medical informatics

[originally in a different format. dunno where this came from. saved 11/22/2004]

A publicationtelemed:
~/wpdocs/WEBSITE/eve.wwwfac.medical_informatics/index.html


Last update March 10, 2004

URL* http://www.albany.edu/medical_informatics*


The MEDICAL INFORMATICS HOME PAGE


*Maintained by Donald F. Parsons MB.BS. , Ph. D. ,* New York State
Department of Health, Albany, NY and the Department of Biometry
and Statistics, School of Public Health, University at Albany,
SUNY, One University Place, Room 150, Rensselaer, NY 12144-3456

*ADVANCED NON-MEDICAL DECISION SUPPORT SYSTEMS (DSS)*
~/wpdocs/DSS/nonmedds version 2.1. May 26. 2004
*WHY DSSs ARE NEEDED IN SO MANY DIFFERENT FIELDS*
The necessity for making decisions "under uncertainty" (using data with
no exact values) occurs in a wide range of different fields. Standard
statistics, fuzzy logic, and unaided human judgement are unreliable.
DSSs have been developed in medicine but are much more extensively
developed in other fields. Human judgement may fail due to:
a. stress and overload of large amounts of data.
b. subtle human judgemental heuristics may be used to reduce the
data load and to postulate a simple model. However, built-in biases may
produce serious errors.
Decision Support Systems (DSSs)have become an essential tool in the
management of many types of complex systems (e.g., manufacturing
processes, control of power plants, administration of a large staff with
diverse training and responsibilities).The DSS is necessary to better
understand such complexity and to identify the biases often present in
human judgement (Druzdzel and Flynn, 2000).
See below for:
*DSS-GENERAL*
* DSS-BUSINESS*
* DSS-MANUFACTURING*
* DSS-GIS*
* DSS-JUDGEMENT***

*SOME HISTORY OF THE DEVELOPMENT OF DSS's IN DIFFERENT FIELDS*
*1955-1960 *(vide. http://mis.postech.ac.kr/topic/dss_e.html) G.W.
Keen and C.B. Stabell in their forward to the Addison Wesley series on
Decision Support, state that "The concept of Decision Support has
evolved from two main areas of research: the theoretical studies of
organizational decision making (Carnegie Institute of Technology during
the late 1950s and early '60s) and the technical work on interactive
computer systems, mainly carried out at the Massachusetts Institute of
Technology in the 1960s." They appear to be referring to work by Herbert
Simon and Allen Newell at Carnegie and research on interactive computing
at MIT by Tom Gerrity.
*1964 *the concept of a DSS was defined by M.S. Morton at Harvard
Business School
*1965* Business Management Information Systems (MIS) began to be
devised for Main-Frame computers about this time.
*1970* Papers about computer-assisted business decision making
began to be published (see the review by Power, 2003).
*1975 *S. Alter devised comprehensive DSS software in his MIT PhD
thesis, "Computer-aided Decision Making in Organizations"
*1978* A Management Information Decision Support System was put
into general use at Lockheed (Georgia.)
*1979*, John Rockart published a ground breaking article in the
Harvard Business Review that led to the development of executive
information systems (EISs) or executive support systems (ESS).
*1981* First international Conference on DSS in Atlanta, Georgia
*1981* Bonczek, Holsapple, and Whinston book "Foundations of
Decision Support Systems." helped institutions develop their own DSS,
*1982 *The book "Building Effective Decision Support Systems" by
Ralph Sprague and Eric Carlson provided a practical overview on the
origins of the DSS concept
* 1985* Executive Information Systems (EIS) and Group Decision
Support Systems (GDSS) began to develop.
*1990* Datawarehousing and On-line Analytical Processing (OLAP,
Datawarehousing and analytical tools) were included into the DSS.
*1993* EIS development more fully includes Datawarehousin.
NB. Even though Fuzzy logic (McNeill and Freiberger,1993) is said
by some to out perform Bayesian networks for some practical
applications, it has attracted little attention in North America.
It is not clear how this intense business and manufacturing DSS
activity spilled out into the clinical world.The theoretical
justification paper of Ledley and Lusted and the early clinical trials
of deDombal were important. Here are the main events:
*1959* Ledley R. and Lusted L Reasoning foundations of medical
diagnosis. Science 130:9-21
* 1968 *F.T. deDombal in Leeds, UK, developed a simple application
of Bayes' theorem to compare the pre-operative diagnosis of abdominal
pain with the post-operative diagnosis. The correct diagnosis improved
from 65-80% to 92% with the Bayes calculation.
*1982 *Internist-1 DSS (later evolved into QMR)
*1972 *HELP at LDS Hospital gave a broad range of DSS help to
hospitalized patients.
1986 QMR (a PC version of Internest-1)
*1987 *Barnett et al. Dxplain
It appears that after the good start made with clinical DSS, there has
been little joint development between the
Business/Management/Manufacturer/Engineer DSS developers and the
Clinical DSS developers. This report suggest some ways in which such
collaborations could startup and benefit all of the developers.

*DSS-GENERAL*
Three components: DBMS, Model-base Management System (MBMS), Dialog
Generation and Management system (DGMS or user interface). Different
kinds of DSS:
*Analytic DSS* gives insight into the decision process
*static-domain model *(disease is in a domain set)
*dynamic decision model* interacts with the decision maker
*learns a model from the statistical data*
*structural equation model:* single independent process in the
system for policy making
Organizations began to build their own DSS. Initially, there was some
unrealistic expectations, but the problem was more with the limits of
the technologies for building DSS than with the limits of the concepts
. Today, a number of disciplines provide the substantive
foundations for DSS development and research. Database researchers have
contributed tools and research on managing data. *Management Science*
has developed mathematical models for use in DSS and provided evidence
on the advantages of modeling in problem solving. Cognitive Science,
especially *Behavioral Decision Making* research has provided
descriptive information that has assisted in DSS design and has
generated hypotheses for DSS research. Some other important related
fields include: *Artificial Intelligence, Human-Computer Interaction,
Simulation Methods; Software Engineering;* and T*elecommunications*.
For more information on multi-disciiplinary applications of DSS see
: "Decision Support Systems: A Review" Druzdel MJ, Flynn RR.2000 In
Encyclopedia
of Library and Information Science. http://www.sis.pitt.edu/~dsl
Decision System Laboratory of University of Pittsburgh. Our Projects
(Structural Modeling, Inference, and Learning Engine) are our research
vehicles and implement most of our research contributions. GeNIe and
SMILE are available free of charge
¨ Environment for Strategic Planning (ESP) (funded by the
Air Force Office for Scientific Research AFOSR) The goal of the ESP
project is to build a computational environment that supports decision
makers in making strategic planning decisions. It covers:
New DSS Techniques
Combining Pre-sorted Data with DSS.
Using expert systems
Using dependable heuristics
Using a simplified model
Preference for particular data or other inputs
Preference for a particular knowledge base
Feeding DSS Results Into Other Types of Analysis
Outcomes analysis of planned system changes
Improvement of human judgement (including reduction of biases
and inconsistencies)
Iteration cycles
Group decision making
Input for non-linear analyzers like Artificial Neural Networks
Also see:
*Power, D.J.A brief history of Decission Support Systems*.
DSSResources.com. World Wide Web,
http://DSSResources.com/history/dsshistory.html. Version 2.8. May 31, 2003.
McNeill D. and Freiberger P.1993.*Fuzzy Logic:* The revolutionary
computer technology that is changing our world.Simon and Schuster, New
York.
************************

*DSS-BUSINESS*
*Business Intelligence Resource Center *
http://www.dimins.com/ResourceCenter/Decision_Support.html
DSSResources.COM (Decision Support Systems Resources) is a web-based
knowledge repository. The mission of this site is to help people who
are interested in learning about how to use information technologies and
software to improve decision making. The target audience is IS
professionals, IS students, managers interested in MIS and academics in
MIS/DSS. This site is needed because Decision Support technology is
evolving very rapidly. IT managers, IS students and academics face a
difficult challenge to stay up-to- date about these changes and to make
good, informed choices about building and maintaining systems to support
decision making in organizations. http://dssresources.com/
***********
This site is designed to help teachers and researchers who choose to
adopt a knowledge management perspective in approaching the field of
decision support systems. "*Decision Support Systems - A Knowledge-Based
Approac*h" is the first book to emphasize this perspective.
http://www.uky.edu/BusinessEconomics/dssakba/
This page provides links to a wide variety of web sites that
complement the coverage in Decision Support Systems: A Knowledge Based
Approach. Links for these related sites are organized into the following
categories: Decision Support Systems, Expert Systems & Artificial
Intelligence, Knowledge Management, Other Related Sites, Related
Organizations http://www.uky.edu/BusinessEconomics/dssakba/relateds....
The DM Review web site offers content from DM Review magazine as
well as online-only articles, resource lists, discussion forums, issue
archives, etc. DM Review focuses on *data warehousing* and related
topics such as *metadata management*. Frequent contributors include such
industry leaders as Bill Inmon, Clive Finkelstein, and Larry English.
http://www.dmreview.com/
*DSSTAR: : Data Mining, Automated Knowledge Discovery, and Decision
Support *- so that YOU can understand and use them successfully. Many
firms have paid thousands of dollars per day for the facts and insights
contained in DSstar. Your competition will read DSstar - shouldn't you?
http://www.tgc.com/dsstar/
*D.J. Power, 'What is a Decision Support System?'* Published in DS,
The On- Line Executive Journal for Data-Intensive Decision Support,
October 21, 1997: Vol.1, No.3 Copyright (C) D.J. Power, 1998.
http://dssresources.com/papers/whatisadss/
*Real World Decision Suppor*t newsletter archives. Real World
Decision support is a FREE newsletter designed to address decision
support issues. There are currently over 12900 subscribers to the
newsletter and the ranks are growing. If you want to see what all these
people are interested in then sign up for the FREE newsletter and begin
to receive in-depth industry articles from leading experts in their
fields. If you are not a subscriber to the newsletter you can subscribe
here. Or you can send an email to webmaster@ewsolutions.com and you will
be added to the list. http://www.ewsolutions.com/newsletter.asp
*Intelligent Enterprise *is the first information resource for
business and IT leaders that focuses on corporate information as a
strategic platform for business advantage. This process is enabled by a
network (increasingly Web- based) of business-critical software
solutions ? what we call the information supply chain ? that store,
manipulate, analyze, and deliver information to the right decision
makers at the right time, and then helps them implement their decisions
across the organization. We provide targeted, in-depth information and
advice, unavailable anywhere else, about the management strategies, IT
architectures, and products involved. Management and technology issues
pertaining to business intelligence (OLAP, data mining, and reporting),
data warehousing, customer relationship management, data and application
integration, knowledge management, and scalable e-business are the bread
and butter of our editorial coverage.
http://www.intelligententerprise.com/ports/search_deci...
Kurt Thearling, Ph.D. *Data Mining,* if you haven't heard of it
before, is the automated extraction of hidden predictive information
from databases. Over the past decade I have been
fortunate to be involved in the creation of a number of commercial data
mining software applications, including Darwin from Thinking Machines
(since acquired by Oracle), Xchange
Dialogue for Modeling, and Pilot Software's Discovery Server. I spent
much of that time focusing on the integration of data mining and other
analytic applications into customer relationship management (CRM)
systems. As Chief Scientist at Wheelhouse Corporation, I focused on
building software infrastructures that would allow CRM systems to work
together. I am currently consulting in areas related to data mining and
CRM. The purpose of this web site is to share information about CRM and
data mining. I hope you find it useful. http://www3.shore.net/~kht/
*Decision Support Systems by Vicki L. Sauter.* Preface: Information
is a crucial component of today's society. With a smaller world, faster
communications, and greater interest,
information relevant to a person's life, work and recreation has
exploded. However, many believe this is not all good. Wurman (in a book
entitled, "Information Anxiety") notes that the information explosion
has backfired, leaving us stranded between mere facts and real
understanding. Similarly, Peter Drucker notes, in a Wall Street Journal
editorial entitled Be Data Literate -- Know what to Know, that although
executives have become computer literate, few of them have mastered the
questions of what information they need, when they need information and
in what form do they need information. Further, Drucker notes,
executives will need better information in the future if their companies
are to be competitive; more information is not the answer unless it is
relevant
information. http://www.umsl.edu/~sauter/book.html
A decision support system (DSS) is a computer program application
that analyzes business data and presents it so that users can make
business decisions more easily. It is an
informational application (in distinction to an operational application
that collects the data in the course of normal business operation).
http://searchebusiness.techtarget.com/sDefinition/0,,s...
Directory of data warehouse, data mining, and decision support
resources. Links to websites are available.
http://www.infogoal.com/dmc/dmcdwh.htm
ITpapers is the Yellow Pages of White Papers, with links to over
25,000 White Papers. A free service, ITpapers enables visitors to find
links to precisely the White Papers they need, quickly and easily, with
summaries and visitor reviews guiding their selection. This page focuses
on Decision Support System white papers.
http://www.itpapers.com/cgi/SubcatIT.pl?scid=216
The *Decision Bot: DSS* Can Benefit from Developments in Robotics.
As the world of decision support gets closer to real time (and in some
areas such as financial trading, many functions do operate in real
time), it?s illuminating to look at a neighboring branch of computing
technology that focuses on the kind of real-time decision making that
ants and other insects depend on for survival: namely, robotics. In this
installment, I describe some of the challenges that robotics researchers
have been tackling, such as representation vs. action, integrated data
and knowledge, multi-perspective state definition, and end-user relevant
benchmark criteria, that relate to the similar challenges DSS developers
face. http://www.intelligententerprise.com/000120/decision.s...
* Decision Support for Management,* 1/e. ISBN 0-13-396268-7 Explores
the variety and richness of support systems ? the wide range of users,
problems, and technologies employed and illustrates how the concepts and
principles have been applied in specific systems. Designed to be a
primary text for understanding this continually developing field ? to
help students and practitioners understand the principles and concepts
that guide the development and use of these systems. The authors include
the full range of systems and users, but with some extra emphasis on
managers and their use of systems such as EIS, rather than an emphasis
on management analysts who develop expert systems.
http://vig.prenhall.com/catalog/academic/product/1,409...
*New TPC Benchmarks for Decision Support and Web Commerce.* For as
long as there have been DBMS's and applications that use them, there has
been interest in the performance characteristics that these systems
exhibit. This month's column describes some of the recent work that has
taken place in *TPC, the Transaction Processing Performance Council*.
http://www.acm.org/sigmod/record/issues/0012/standards...
*CompInfo - The Computer Information Center *-The top one-stop
reference resource for corporate IT, computers and communications.
Millions of IT users world-wide rely on our Web-based support resources.
Tell your colleagues and friends, and bookmark us at
http://www.compinfo-center.com...check out our technical knowledge bases
and on-line resource center. http://www.compinfo-center.com/tpeis-t.htm
*INFORMS Online Bookstore: Decision Support Systems.* The interest
in Decision Support Systems comes from many different perspectives.
Some, especially in this community, are most interested in the models
and model management features of DSS. Others are more interested in the
dynamics associated with Group Decision Support Systems. Still others
are most interested in the enabling concept of Data Warehousing. Hence,
the books are grouped according to what interest area they best meet.
http://www.informs.org/Bookstore/dss.html
Welcome to the ISWorld page for Decision Support Systems Research.
This page is intended to provide a useful starting point for accessing
WWW-based material related to the design,development, evaluation, and
implementation of Decision Support Systems (DSS).
http://www.uni.edu/dss/isworld/dss.html
A Medical Infromatics contribution. *Modeling for Decision Support
by Mark A. Musen, M.D., Ph.D.* Appeared in *Handbook of Medical
Informatics, J.H. van Bemmel and M.A. Musen, editors, Springer-Verlag,
1997.* Decision support programs come in many forms. Many, such as QMR
(see section 3.3), are standalone applications that users access via
personal workstations or via the Internet...
http://www-smi.stanford.edu/pubs/SMI_Reports/SMI-98-07
Current Issue of DMReview Magazine http://www.dmreview.com/issue/
Stay Informed: Industry Events. View all events by category: *Analytic
Applications; *ASP/BSPB2B Analytics; *Balanced Scorecard*; *Business
Intelligence*; CRM; DAMA; *Data Mining*; *Data Quality*; *Database
Marketing*; Databases; DW *Administration,* *Mgmt.*, *Performance*; DW
Basics; DW Design, *Methodology;* *DW Engines,* Exploration Warehouse;
DW Performance; E- Business; E-Commerce; E-Intelligence; Enterprise
Application Integration (EAI); Enterprise Information Portal (EIP);
Enterprise Intelligence; *Enterprise Performance Mgmt*.; ERP;
*Healthcare Industry;* *Meta Data;* *Middleware;* *Privacy; Security;
Storage; Supply Chain; Telecommunications *- Telco Industry;
Wireless/Mobile; XML. If a category of interest is not listed, it means
we are not aware of any events within that topic.
http://www.dmreview.com/events/
International Conference on Decision Making and Decision Support in
the Internet Age 4th of July, 2002 - U.C.C, Ireland
http://afis.ucc.ie/dsiage2002/
*************************************

*DSS-MANUFACTURING*
*Rensselaer Polytechnic Institute* *Department of Decision Sciences &
Engineering Systems (DSES)* (518) 276 8227 | Email: dses@rpi.edu
http://www.rpi.edu/dept/dses/www/research/tech_reports.htm
DSES has established strategic research thrusts in two key areas:
*Intelligent Manufacturing and Service Systems (IMASS) *and *Data Mining
and Decision Support Systems (DMADS*). IMASS refers to the development
of quantitative- and knowledge-based tools for the analysis and design
of systems which manufacture products, provide service and/or distribute
goods and services. In DMADS, computationally powerful tools (including
statistical computing, fuzzy logic, neural networks, genetic algorithms,
cluster analysis, chaos theory, data visualization and simulation) are
applied to data to ascertain the underlying structure or knowledge base.
In this way, valid decision models can be developed. Research projects
in which DSES participates include the Electronics and Agile
Manufacturing Research Institute, the Center for Services Research and
Education and the Rensselaer Statistical Consulting Center.
Example Project Reports for 2003
* *Natural Language Interaction* Using a Scalable Reference Dictionary
V. Boonjiing, C. Hsu
* Trends in En Route Effects Along *Selected Airways * T.R.
Willemain, N. YakovchMonte
* Monte-Carlo Comparison of Estimation Method for Additive Two-Way
Tables N. Yakovchuk, T.R. Willemain
* A Mathematical *Model for Warehouse Design and Product Allocation*
S.S. Heragu, J.C.S. Huang, R.J. Mantel, P.B. Schuur
* Analysis of a Multi-class Manufacturing System via Semi-open Queuing
Networks T. Coenen, S.S. Heragu, W.H.M. Zijm
* Two-level *Manufacturing System Performance Analyzer* G.
Meng, S.S. Heragu, H. Zijm
* Clustering based order picking sequence algorithm for an a*utomated
warehouse* B-I. Kim, S.S. Heragu, R.J.Graves
* Learning to Design and Analyze Materials Handling Systems: Developing
Multimedia Tools S.S Heragu, S. Jennings
* Restoration of *Services in Interdependent Infrastructure Systems:* A
Network flows Approach E.E.Lee,II, D.J.Mendonca, J.E.Mitchell,
W.A.Wallace
************************

*Web-based DSSs* Daniel.Power@dssresources.com) is Professor of
Information Systems at the University of Northern Iowa, and editor of
DSSResources.COM, URL
http://dssresources.com.This is version 4.2. It was last updated June
15, 2002. Version 1.0 was published on the Web July 3, 1996. This Web
page should be cited as: Power, D.J. Decision Support Systems Web Tour.
World Wide Web, http://dssresources.com, version 4.2, June 15, 2002.
http://dssresources.com/tour/dsstour.html
Decision Support Systems (DSS) are a specific class of computerized
information system that support decision-making activities. DSS are
interactive computer-based systems and subsystems intended to help
decision makers use data, documents, knowledge and/or models to identify
and solve problems and make decisions. DSSResources.COM uses an
organizing framework with five major DSS types or categories:
*Communications-Driven DSS,*
*Data-Driven DSS,*
* Document- Driven DSS,*
*Knowledge-Driven DSS* and
* Model-Driven DSS.*
A major focus at DSSResources.COM is resources on how to implement these
types of DSS as Web-Based DSS..
The Decision Support Systems Hyperbook and other resources in the
Subscriber Zone at DSSResources.COM provide the most up-to-date text and
reference materials on DSS.
University and Research Web sites related to DSS
*DSS case studies on the Web*
DSSResources.COM has many DSS case studies in its on-line Library. Also,
the Data Warehousing Institute (URL http:// www.dw-institute.com) has
case studies prepared by "users" of a specific DSS. Additionally, many
DSS software vendors provide case studies (customer success stories) of
successful decision support implementations at their web sites. Some of
the case study material on the web is very detailed, including
quotations from managers in companies that installed a specific DSS,
while other case examples are very brief.
**********************
*NEW FRONTIERS OF DECISION MAKING FOR THE INFORMATION TECHNOLOGY ERA*
http://www.wspc.com/books/business/4416.html edited by Yong Shi
(University of Nebraska, Omaha) & Milan Zeleny (Fordham University, New
York)
*Behavioral Issues in Decision Making*
*Multiple Criteria and Decision Support Systems*
*Objective Space Analysis*
*Risk and Efficiency Management*
*Tradeoff Analysis in Decision Making*
*Data Environment Analysis*
*Multiple Criteria System Engineering*
*Multiple Criteria Applications*
440pp Pub. date: May 2000 ISBN 981-02-4299-9 US$84 / £57
*********************************
*LINUX to the RESCUE!*
Silicon Graphics Inc Linux Servers and workstations
SGI.http://www.sgi.com/insider/03_jan/
Scaling Linux to New Altitudes The SGI Altix 3000 family of servers and
superclusters employs scalable 64-bit Linux clustering to create what is
simply the world's most powerful open-source computing environment with
an optimized Linux software environment that scales to hundreds of
Intel® Itanium® 2 processors, with up to 64 processors in a single Linux
node. Offered exclusively for its SGI® AltixTM 3000 family of servers
and superclusters, SGI's software environment also offers a unique
capability for Linux clusters--global shared memory across cluster
nodes--raising the bar for open source computing and creating the most
powerful Intel Itanium 2 processor based computing environment in the
marketplace.
A key component of SGI's software suite is SGI ProPackTM, a new set of
high- performance Linux optimizations that enhances overall system
scaling, data handling and resource management while maintaining binary
compatibility with existing 64-bit Linux applications running on the
Intel Itanium 2 processor.
Optimized for users in physical and life sciences, manufacturing,
oil and gas, and government and defense markets, this powerfully
enhanced environment includes features never before available on Linux.
The SGI enhancements to Linux support the third-generation SGI®
NUMAflexTM architecture and modular system interconnect, allowing users
to further scale these powerful systems to hundreds and even thousands
of processors by combining the computing power of multiple systems into
superclusters capable of tackling the most complex computing problems.
For example, life sciences researchers could accelerate their drug
discovery analytical runtimes by a factor of 10 by taking all of their
genomics databases off of disk and into hared
memory. Currently, many of these analyses take several weeks as
researchers assess potential compounds sequentially against dozens of
genomics databases in a traditional distributed memory Linux cluster. By
simultaneously putting all databases into memory, researchers can reduce
their runtimes to a matter of days, thus requiring far fewer processors
and overall compute cost. SGI® Decision Support Center: Finding the few
important bits of information out of mountains of data is the job of the
SGI Decision Support Center solution.
. Human visual perception is dominated by the sense of sight, so the
ability to visually represent data is the key to turning data into
information. which uses large-scale visualization, high-performance
computing, and the management of complex data to provide
mission-critical information to support rapid and confident decision-
making cycles. DSC acts as a data fusion engine that lays out massive
amounts of vital information in a real-time virtual visual panorama to
help decision makers see the big picture and focus on making the right
decisions. In order for something to be called a decision support
center, it must improve the decision-making process. Improvements can be
measured in time (making faster decisions), quality (making better, more
informed decisions), and confidence (making the right decisions). .In
the area of homeland security, SGI is working with its partners to
develop a solution for decision support and communications called the
Nuclear, Biological, and Chemical Threat Operation and Training Center
(NBCOTC).
SGI announced leadership in Linux for technical computing with an
optimized Linux software environment that scales to hundreds of Intel
Itanium 2 processors, with up to 64 processors in a single Linux node.
****************
*ISWorld Decision Support Systems Research Page * Section Editor:
Daniel Power Co-Editors: Hemant Bhargava and Freddie Quek
http://www.uni.edu/dss/isworld/dss.html
Welcome to the ISWorld page for Decision Support Systems Research. This
page is intended to provide a useful starting point for accessing
WWW-based material related to the *design, development, evaluation, and
implementation of Decision Support Systems (DSS).*
DSS Definitions, Resources and References
This section assists you in accessing information about DSS concepts,
DSS books, major DSS journal articles (especially literature reviews),
and a brief historical narrative on the foundation of DSS research and
practice. We are open to your ideas and suggestions. Please help us
build ISWorld Net!
Brief History of Decision Support Systems (maintained by D.
Power)
DSS Articles On-line (maintained by D. Power)
DSS Books with search capability (maintained by D. Power and
P. Gray)
DSS Book Reviews by P. Gray
DSS Glossary (maintained by D. Power)
DSS Research Topics
DSS Web Tour (by D. Power)
Mathematical Programming Glossary (maintained by H. Greenberg)
Spatial DSS page (maintained by P. Keenan)
*Software Resources*
This section assists you in accessing information about DSS software. It
contains links to software archives and reviews. We are open to your
ideas and suggestions. Please help us build ISWorld Net!
*DecisionNet* is a joint project developed by Hemant Bhargava
and Ramayya Krishnan"It offers access to a distributed network of
modeling and decision support systems. It allows providers of modeling
and decision support services to have their technologies (data, decision
models, algorithms, and decision support packages) publicised, browsed,
and executed over the WWW. DecisionNet enables consumers of decision
technologies to search an index of technologies, connect to selected
technologies, and use them by providing information specific to their
problem."
*Directory of Software for Belief Networks*. (maintained by
Russell Almond) It "describes software for processing graphical belief
function models, and related modes such as Bayesian networks, influence
diagrams, and probabilistic graphical models." ... "Each entry ...
contains information about features of the software and contact
information. Pricing information includes the date the price was last
updated as this information may vary from time to time. Hyperlinks take
you to demo versions (or actual software for free software) when it is
available on-line.
* DSS Spreadsheet Links* (maintained by D. Power)
* Major DSS Information Links* This section contains links to major
WWW sites that provide useful information relevant to DSS research.
DSSResources.COM (maintained by D. Power)
*General DSS Related WWW Links * University DSS Links What's
New at DSS Resources?
*Data Warehousing Information Center *(maintained by Larry
Greenfield) "The purposes of this site are to: help locate vendors of
tools to build, access, and manage data warehousing and decision
support systems, point to many other sources of information", and
provide general information about data warehousing and decision support
systems.
*Operations Research Page* (maintained by M. Trick) This is an
impressive collection of links and materials related to operations
research.
*Other DSS-related Resources and Services*
*DSS Announcements* (maintained by C. Holsapple)
*DSS Researchers Home Page Directory *(maintained by D. Power)
IFIP WG 8.3 Home page maintained by G. Widmeyer
IFIP-8.3 Membership Database maintained by F. Quek
ISWorld DSS Teaching Resources page, editors D. Power, H. Bhargava
and F. Quek
ISWorld DSS Research page
The URL for this page is http://www.uni.edu/dss/isworld/dss.html
Daniel Power who can be reached at the email address daniel.power@uni.edu.

************************************
* 3 DSS AS A TOOL FOR THE WATER RESOURCES PLANNING AND MANAGEMENT*
http://www.nic.gov.jo/inwrdam/dss.html
DSS have wide applications in water resources management and in the
water industry because problem resolution in these fields involves
significant judgment and experience. Although the development of complex
and deep expert systems with their requirements for knowledge
engineering can be very costly, their potential are obvious.
DSS are used in many water resources planning and management
applications like:
Operation and management of water supply systems;
Complex hydrologic /hydraulic models;
Urban drainage using storm water management model;
Operation and control of activated sludge plants;
Cost /tariff modeling;
Crisis and disaster management.
An important issue while describing the applications of DSS is the usage
patterns which means, who should use a DSS, for what problems, at what
intervals, through what mechanisms, and to what end. The types of
problems for which DSS are appropriate are those which are
semi-structured, that is not completely structured at one or more of the
problem solving phases, design or choice and are most a
*****************
*A decision support system for local administration in GIS
environment *- A study at Paramakudi
Taluk of Ramanathapuram district, Tamil Nadu
The amount of data generated by the government in this digital era is
phenomenal. Attempts to process the data and rendering it as readily
usable information by application of a powerful integrated approach such
as GIS are not widespread. Contemporary decision-making is complex and
involves a wide spectrum of knowledge sourced from diverse fields. The
impacts of a decision thus made over an even more complex social fabric
necessitate the use of sophisticated Decision Support Systems (DSS). The
unique capability of a Geographic Information System (GIS) is that not
only it can act as a database but also as a powerful tool, wherein
complicated operations can be performed with greater ease and better
quality information gleaned. When incorporated in this environment,
*************************
* DSS-JUDGES*
*JUDICIAL DECISION SUPPORT SYSTEMS *FROM A JUDGE'S PERSPECTIVE
A Presentation at the Seventh National Court Technology Conference
(CTC7), Baltimore, USA, August 14-16, 2001. By STEIN
SCHJOLBERG, Chief Judge, Moss Byrett, Norway
From a judge's perspective we have welcomed the information technology
into courthouses and courtrooms, as a part of the administrative tools
handling case files, court calendars, electronic filing, e-courts and
cybercourts. The First International Workshop on Judicial Decision
Support Systems (JDSS) was held in Melbourne, Australia in 1997, and the
Second Workshop in Oslo in 1999. The Third Symposium was held at the
Chicago-Kent College of Law in Chicago, in May 2001.
At the conference in Chicago judges and researchers from 7 countries
participated and presented many papers on a variety of subjects. the
Donald Berman Laboratory for Information Technology and Law, La Trobe
University, Melbourne, Australia, headed by John Zeleznikow. It has a
long history of building Legal Decision Support Systems in conjunction
with Victoria Legal Aid in Australia. In building such systems they
have developed tools for placing the systems on the Web. With these
tools they have 1. Split-Up -the distribution of property
following divorce in Australia. It uses knowledge
discovery from databases techniques to learn how
**********************************************
.*http://dssresources.com/ Very good resources !!*
*********************
**** Appendix ****
*DSS GLOSSARY*
*Enterprise-wide DSS* A DSS that supports a large group of
managers in a networked client-server environment with a specialized
data warehouse as part of the DSS architecture.
*Group Decision Support Systems (GDSS*) An interactive,
computer-based system that facilitates solution of unstructured problems
by a set of decision-makers working together as a group. It aids
groups, especially groups of managers, in analyzing problem situations
and in performing group decision making tasks.
*Executive Support Systems (ESS) * An executive information
system (EIS) that includes specific decision aiding and/or analysis
capabilities.
*Groupware * Is software designed to support more than one
person working on a shared task. Groupware is an evolving concept that
is more than multiuser software which allows access to the same data.
Groupware provides a mechanism that helps users coordinate and keep
track of on-going projects. It allows people to work together through
computer-supported communication, collaboration, and coordination. Lotus
Notes, Microsoft Exchange, Communicator, Novell GroupWise, Netscape
SuiteSpot, Eclipse, Team Talk, and Internet Explorer/NetMeeting are
examples of groupware products.
*Prototyping *A strategy in system development in which a
scaled down system or portion of a system is constructed in a short
time, tested, and improved in several iterations. A prototype is an
initial version of a system that is quickly developed to test the
effectiveness of the overall design being used to solve a particular
problem. Prototyping is similar to the *Evolutionary (Iterative)
Design Process.* It is sometimes termed rapid prototyping and is similar
to rapid
application development (RAD).
*Web-based DSS * A computerized system that delivers decision
support information or decision support tools to a manager or business
analyst using a "thin-client" Web browser like Netscape Navigator or
Internet Explorer. The computer server that is hosting the DSS
application is linked to the user's computer by a network with the
TCP/IP protocol.
***********************************
*Scope of Journal of Decision Support Systems and Electronic Commerce*
Contributions on the concepts and operational basis for DSSs, techniques
for implementing and evaluating DSSs, DSS experiences, and related
studies. May draw-on, such diverse areas as artificial intelligence,
cognitive science, computer supported cooperative work, data base
management, decision theory, economics, linguistics, management science,
mathematical modeling, operations management psychology, user interface
management systems, and others. The common thread of articles published
in the journal will be their relevance to theoretical, technical DSS
issues. There are six topic departments:
1. *DSS principles, concepts, and theories; frameworks, formal
languages, and methods for DSS research*; tutorials about the nature of
DSS; assessments of the DSS field.
2. *DSS Development-Functionality.* e.g. methods, tools, and
techniques for developing the underlying functional aspects of a DSS;
solver/model management; data management in DSSs; rule management and AI
in DSSs; coordinating a DSS's functionality within its user interface.
3. *DSS Development-Interfaces*. e.g. methods, tools, and
techniques for developing the overt user interface of a DSS; managing
linguistic, presentation, and user knowledge in a DSS; DSS help
facilities; coordinating a DSS's interface events with its functionality
events.
4. *DSS Impacts and Evaluation.* e.g. DSS economics; DSS
measurement; DSS impacts on individual users, multiparticipant users,
organizations, and societies; valuating/justifying DSSs.
5. *DSS Reference Studies.* e.g. reference discipline tutorials for
DSS researchers; emerging technologies relevant to DSS characteristics
or DSS development; related studies on such topics as communication
support systems, computer supported cooperative work, negotiation
support systems, research support systems, task support systems.
6. *DSS Experiences, Management, and Education.* e.g. experiences
in developing or operating DSSs; systems solutions to specific decision
support needs; approaches to managing DSSs; DSS instruction/ training
approaches. http://www.elsevier.com/homepage/sae/orms/dss/menu.htm
*
*Decision Support Systems Volume 33,* Issue 2 , June 2002, Pages 105-110
*DSS: directions for the next decade *C. Carlsson, E. Turban,
Finland, Hong Kong managerial decision-making processes. the term DSS
itself is seen less frequently . Instead, terms such as business
intelligence and OLAP
Modern corporations objective is to create business entities, which are
leaner, more flexible and more responsive to a rapidly changing business
environment.
The first target for new generation of DSS technology should be the
overwhelming flow of data, .Software agents (also called intelligent
agents) have been designed and implemented to take care of the
screening, sifting and filtering of data, information and knowledge.
These Java-built components can be designed and implemented to search
for data sources with user-defined search profiles, to identify and
access relevant data, to copy the data and to organize and store it in a
data warehouse.
Other agents of the same "family" can then be used to retrieve the data,
insert it in reports and to distribute it over e-mail according to
topic-specific distribution profiles.
Soft computing includes research on fuzzy logic, artificial neural nets,
genetic algorithms and probabilistic modeling. The added feature to the
intelligent systems is that in soft computing, the machine-learning
systems are developed using fuzzy logic and the fuzzy set theory as a
theoreticaland methodological basis.
collaborative learning in virtual DSS classes where students from
different universities and even different countries will collaborate in
solving complex managerial problems as part of their learning experiences.
The papers The first paper, the major change that occurred in DSS due
to the introduction of data warehousing and data mining as major
facilitators of DSS and due to today's Web-based DSS. The authors
conclude that Web- based systems can be built today with less cost and
increased functionalities.
The third paper, written by Nemati et al., looks at the integration of
decision support, knowledge management and artificial intelligence in a
data-warehousing framework. The paper describes some of the tools,
including commercial ones, which can facilitate the process. Of special
interest is the use of natural language-generated arguments concerning
the validity of the models, meta-models and new knowledge created in
this process.
References
3. M.J. Shaw , Electronic commerce: review of critical research issues.
Inf. Syst. Front. 1 1 (1999).
************************************************
*SUGGESTIONS FOR OBTAINING INTERACTION BETWEEN CLINICAL AND NON-CLINICAL
DSS DEVELOPERS*
* 1. A decision support system journal invites clinical DSS papers
for up to 25% of space in its issue.*
* 2. A private, secure web site that allows both mixed clinical and
non-clinical submissions and encourages private questions and assistance
for using the method in the opposite setting.*
* 3. A 2-day symposium at the NIH Washington. Supported by both NIH
and NSF funds.*
********************
PLEASE E-MAIL ME YOUR COMMENTS: dfp10@wadsworth.org Version 2.1 May
25, 2004. D.F. Parsons
######################################################


The Clinical Electronic Notebook (CEN) Project A collaborative
project with the US Department of Energy PacificNorthwest National
Laboratory [PNL]
h*ttp://collaboratory.emsl.pnl.gov/elnotebooks.html.*


This project is also a part of a new SUNYLearning Network
(Internet) Medical Informatics course now being devised: The Linux
Medical Informatics Practicum (Graduate, 3 credits, the Albany
School of Public Health). Students will be required to download and
install Linux onto a PC. There are now many free statistical, public
health, statistical and probability programs available in Linux.


* The first objective is to make available paperless,
clinical record books that meet international medico-legal standards
for security*, stability, and privacy. The notebooks must enable
easy exchange of clinical data with Hospital Information Systems,
other clinical networks and terminals, and also with Personal
Computers and palmtops. Current development uses the SPARC Solaris
and SuSE Linux Operating Systems. Subsequently, it will be ported to
other OSs. The system can work with secure local and remote Web
servers (Apache with TomCat as java servlet server). SAM1.1
(Scientific Annotation Middleware), as developed by the PNL
Principal Investigator for enotebook collaborations, James Meyers,
is being used to access files and databases with password
verification. Most of the configuration of the system uses XML
files. For example, the $tomcat/webapps/sam.xml file defines the
configuration of notebooks. The $tomcat/webapps/Domain.xml file
defines the registration, security and access of different classes
of clinical users.


Other SAM files contain examples of client Clinical
Electronic Notebooks (CEN) that can be adapted by new users. The
CEN follow the general configuration schemes of the PNL client,
physics Electronic Laboratory Notebooks (ELN). The PNL
Collaboratory site
(http://collaboratory.emsl.pnl.gov/elnotebooks.html) provides
instruction in the setup and use of example notebooks such as the
current ELN5.1 client enotebook.


The second objective is to add online clinical tools to
enotebooks when connected to Hospital Information Systems. A
Decision Support System is planned for diagnosis and therapy, and
the statistical analysis of clinical data will be repeatedly updated.

*Much can be learnt from the current uses of enotebooks (mostly in
physics and chemistry). The experiences of these users will help guide
the development of clinical enotebooks.*

*****************************************


The Fall 2005 (3 credit) Undergraduate SLN DISTANCE LEARNING COURSE
in MEDICAL INFORMATICS .


Offered by: The School of Public Health, Department of Biometry and
Statistics, the University at Albany, Albany, NY. Taught by: Don
Parsons Credits: 3


SLN Course Description (*click on
Fall2005-Course List, and then Start Dates*)


Medical Informatics: medical reasoning and decision making, medical
language and classifications, information databases, Hospital
Information Systems, healthcare networks, patient records,
physiological signal processing, medical imaging, Decision Support
Systems, Computer Assisted Instruction, patient monitoring, nursing
informatics and research, security for patient data, analysis and
control of medical activities, evidence-based medicine and
literature searching. Outcomes analaysis .


Registration and other information:
(Click on "About the
Suny Learning Network"). Information about how to use your computer
in the course is given in the FAQ (Frequently Asked Questions).


Other questions: call 800-875-6269 or email helpdesk@SLN.suny.edu.


OR:


Obtain the SLN Fall 2002 Brochure (which contains the same
information, the FAQ, and the registration forms) by calling
800-875-6269.


* * *OTHER TOPICS on this MEDICAL INFORMATICS HOME
PAGE:*

* *Local (central New York State) medical informatics resources and
activities*

* *The School of Public Health, Department of Biometry and
statistics. Medical Informatics course H STA571*

* *Review of "Handbook of Medical Informatics" edited by J.H. van
Bemmal and M.A. Nusen, Springer, 1997.*

* *Albany Medical College Medical Decision Making Interest Group,
telemedicine network*
* *Bassett Healthcare, Cooperstown, NY. Telemedicine network.*
* *Nursing Medical Informatics.*
* *Regional Nursing Informatics*

* *Western New York State*

* *University at Buffalo Health Sciences, Medical Informatics
courses. Telemedicine network.*
* *University at Rochester Medical Center, Division of Medical
Informatics*

* *Mid-Hudson/New York City*

* *Columbia University, Department of Medical Informatics*
* *Mid-Hudson Valley Health Care and Medical Informatics Cluster*
* *The University at Stony Brook Medical Center*

* *Selected public health Web sites*
* *Selected medical informatics Web sites*

* *Computer Assisted Instruction (CAI)*
* *Broad medical resource sites*

* *An Open Discussion on Improving the Status of Medical Informatics
Teaching, Research and Service in New York State (use the e-mail
form at the bottom of this page to mail your comments to Don Parsons.*
* *Useful Medical Informatics Resources grants click HERE

(URLs, Mailing Lists, UseNet NewsGreoups, MI Training Sites, etc)
click HERE
*

*LOCAL (CENTRAL NEW YORK STATE : ALBANY, SCHENECTADY, & TROY REGION)
MEDICAL INFORMATICS ACTIVITIES*

* *University at Albany SCHOOL OF PUBLIC HEALTH: H STA571 Topics in
Medical informatics*
* Spring, 1999. Three credits, Call Number 7135, Requires SKN,
approval of the instructor: Donald F. Parsons MD, PhD. (518)
474-7047, Fax: (518) 474-8590. dfp10@telemed.wadsworth.org. Meet
Tuesdays and Thursdays 9:45-11:05 am in Room C6, the University
at Albany School of Public Health, East, Rensselaer Campus. 26
lectures/demonstrations: *For a detailed syllabus click ** here.
* **
Medical Informatics is the information science of computer
optimization of the transfer and interpretation of health care
data. It has a special emphasis on analyzing and supporting the
medical decision process. It provides an unusual opportunity for
people with diverse backgrounds (medical residents and students,
students of public health, nursing, computer science, business
computing, health care administrators, physics and engineering in
relation to patient monitoring devices) to be involved in
improving the manipulation of clinical data.
* Topics covered (in brief): Computers and programming in medicine,
the probability and statistical principles involved, Decision
Support Systems (DSS), the types of medical data and the
Computer-based Patient Record, efficient searching and data
mining of large health care databases (including medical
literature, clinical trial databases, and knowledge databases).
Also, Hospital Information Systems (HIS), Clinical Laboratory
Information Systems (LIS), telemedicine, teleradiology, and
Picture Archiving and Communication Systems (PACS).
Telecommunication between county and state health departments
using Web site technology. Instruction in writing HTML pages and
in medical use of the Internet. Security of patient clinical
data. Medical Artificial Intelligence , patient monitoring
devices, expert systems and production rules. Use of Bayesian
probability, fuzzy logic and artificial neural networks for the
calculation of the probabilities of differential diagnoses and of
outcomes of different treatments. Statistical analysis of global
outcomes. Nursing informatics systems, information processing of
nosocomial hospital infections. Authoring interactive Computer
Aided Instruction (CAI) courses. Distance learning techniques
using static (conventional) HTML pages and using dynamic Domino
servers with Notes databases. Some lectures are
contributed by other faculty of the School of Public Health, the
Albany Medical College, the New York State Department of Health
and the Informatics Sciences Department of the University at
Plattsburgh. Students receive summaries for each of the 26
lectures. The textbook is: "Introduction to Clinical Informatics"
by P. Degoulet and M. Fieschi. Springer Verlag . 1997. ISBN
0-387-94641-1.
* Review of a new book for the above course: *HANDBOOK of MEDICAL
INFORMATICS
edited
by J.H. van Bemmel and M.A.Nusen, *Springer, 1997.
* *ALBANY MEDICAL COLLEGE:*
* *URL:http://www.amc.edu*

* *The Capital District Medical Decision Making Interest Group.
*Meets monthly at the Albany Medical College. For information and
to be placed on the mailing list, e-mail
jchessare@ccgateway.amc.edu or phone (518) 262-3589.
* *Telemedicine for the AMC rural consortium: *One of the largest
networks in the region.

* *BASSETT HEALTHCARE:*
* Grants from the Rural Electrification Administration, The Health
Resources and Services Administration, and NY State Department of
Health helped establish a telemedicine network to more than 20
regional medical sites including 3 rural hospitals. The links
provide improved access to specialty care ,and better access to
education and training. Uses the "Picasso" video-consulting system
with telephone line connections.
* Bassett Healthcare collaborates with the C. Everett Koop Institute
at the Dartmouth-Hitchcock Medical Center and the American Academy
for Cerebral Palsy and Developmental Medicine in teleconferences
for disablility patients. Also, the smaller hospitals of the
region have used telemedicine to link their Emergency Rooms and
visiting nurses of the region are also linked. For more info on
telemedicine call Martha Gorman at (607) 547-3917 or e-mail at
telemed@telenet.net or the Web site at
*http://www.bassetthealthcare.org*
* *REGIONAL NURSING INFORMATICS*:
* You can obtain nearly all the local and national informatics
information from the home pages of two local male nurses who have
a strong interest on nursing informatics:

* W. Scott Eardley MS, RN *http://www.acsu.buffalo.edu/~erdley
*
* David Curry RN-C, MSN *http://www.plattsburgh.edu/nur/curry.htm*

* Also, the on-line Journal of Nursing Informatics and other nursing
journals can be reached
at:*http://ublib.buffalo.edu/libraries/e-resources/*
*

------------------------------------------------------------------------

*WESTERN NEW YORK MEDICAL INFORMATICS ACTIVITIES*

* *University at Buffalo Health Sciences Medical informatics:*
* *BPH-572-0 MEDICAL INFORMATICS AND BIOMEDICAL APPLICATIONS *2
credits; spring semester. Dr. R.A. Spangler and staff. This course
introduces a range of applications of computers in medicine and
biomedical research with emphasis on the ways in which computer
technology can contribute to the solution of medical and
biomedical problems. "Hands-on" experience in the use of a variety
of software tools. Students become involved in a faculty project
in one of the following areas: (1) hypermedia knowledge base
development; (2) natural language processing; (3) medical imaging
processing; (4) microscopic image processing; (5) dynamic
simulations of biological systems; and (6) applications of
parallel distributed processing.
* *BPH-603-0 MEDICAL BIOPHYSICS* 2 credits; fall and spring
semesters-half the class takes course in fall, half takes it in
spring. *Required course for sophomore medical students.* This
course introduces the basic biophysical principles of diagnostic
and therapeutic techniques and demonstrates the technology
utilized in modem medical practice. The second-year medical class
is divided into groups of 20 students, and each group is
supervised by a preceptor. The groups are introduced to the topics
of: radiology; radiobiology and radiation therapy; ultrasound;
electrobiological techniques; computer techniques and applications
in medicine; prosthetic devices; and imaging techniques such as
nuclear medicine, magnetic resonance imaging, and
computer-assisted tomography. In each topic area, there is a
preliminary session in which the basic biophysical principles of a
technique are examined through discussion, demonstration, and
laboratory procedure, followed by a clinical demonstration in
which the application of these principles is illustrated in a
clinical setting and discussed by clinicians experienced in its
use. Upon completion of the course, the student should be able to
correlate the fundamental biophysical principles with the clinical
utility of the technique, and thus appreciate the advantages and
limitations of advanced technologies used in particular procedures*.*
* *BPH-607-0 PRINCIPLES OF CLINICAL BIOPHYSICS I *and *BPH-608-0
PRINCIPLES OF CLINICAL BIOPHYSICS II* 3 credits each; fall and
spring semesters (every second year). This course, offered to
medical students and graduate students in electrical engineering,
physics, and biophysics, is intended to familiarize them with the
advances in medical technology as well as with the underlying
principles of physics and engineering. The course emphasizes the
application of existing and forthcoming technology to medical
problems. BPH-608-0 is a continuation of BPH-607-0, which covers a
different set of topics, including the use of ultrasound, electric
pacing of the heart, diagnostic radiology, including computerized
tomography, magnetic resonance imaging, positron emission
tomography, radiation therapy, and intensive care instrumentation.
Students taking this elective course will understand the physics
and engineering methodologies that allowed the design and
development of the large variety of current medical technology.
This will not only enable them to attain better and more
meaningful use of the different instruments they will apply in
their clinical practice, but they will also be able to communicate
with physicists, engineers, or other technologists when trying to
adapt or improve the performance of existing instants or to design
and construct new diagnostic or therapeutic biophysical tools. The
best candidates for this course will be medical students who
majored in college in electrical, mechanical, or chemical
engineering, as well as in physics or the computer sciences. The
course includes hands-on experience with different instruments. It
also includes discussions of various clinical situations which
call for technological approaches, emphasizing the rationale of
selecting a certain technology-based strategy for a given clinical
problem. URL: *http://rpci.med.buffalo.edu/~graded/edbiophy.html
*
* *University of Rochester Medical Center, Division of Medical
Informatics:*
* The Division of Medical Informatics is a group of medical faculty
and computer experts whose functions are to provide the school
with an increased awareness of the breadth and depth of computer
applications in medical practice and medical education. Also, to
promote the incorporation of these new techniques into the life of
the institution; and to develop advanced applications of computers
in medicine and medical education. The Division provides
curriculum supplementation through computer-assisted learning
modules, elective opportunities and introductory class exercises.
The Division collaborates with, and supports, the medical school
faculty in the development of in-house, customized, computer-based
coursework. The Division has ongoing projects with a number of
academic units including medicine, microbiology and immunology,
neurobiology and anatomy, neurology, obstetrics and gynecology,
pathology and laboratory medicine, and physiology.
* The Division has state-of-the-art workstations with high
resolution graphics displays and sound and interactive video
capabilities. These workstations can be used by students and
faculty for courseware development, image processing, world wide
web, and/or artificial intelligence projects which are consistent
with the goals of the Division. The Division maintains a student
laboratory consisting of twenty networked Macintosh computers,
which are used for whole class or small group exercises and for
independent study. The Division provides e-mail services for
medical students and Medical Center graduate students as well as
network access to educational materials for the computer facility
URL: *http://www.urmc.rochester.edu/SMD/MedInfo/MedInformatics.html*

_______*_______________________________________________________________________________________________________________*


*MID-HUDSON / NEW YORK CITY MEDICAL INFORMATICS ACTIVITIES*

*Columbia University, Department of Medical Informatics. *Paul
Clayton, Ph.D. Chair, Department of Medical Informatics. Professor,
Medical Informatics, Medicine, and Radiology, and Director of Computer
Information Systems. "Our Mission is to perform innovative research
and development which will enhance the nation's ability to support
health care cost containment and improve the quality of health care
delivery. " Research topics include: medical vocabularies and medical
language processing, information resources for clinical research,
Arden syntax for Medical Logic Modules, cholesterol guidelines, OB/GYN
toolbox. Also, knowledge structures to support Medical Decision Making
(James Cimino); Computerized Pulmonary Monitoring Center (CPMC2);
Integrated Mammography Information Management System; Immunization
Registry. It is also a New York State supported Center for Advanced
Technology (CAT).URL: *http://www.cpmc.columbia..edu
*

*Mid-Hudson Valley Health Care and Medical Informatics Cluster:
*Situated midway between Albany and NYC. It will explore the market
opportunities in health care. Steering Committee includes Columbia
University and the Association of University Technology managers (AUTM)
and is a National Technology Transfer Center. (212) 305-2944
dl330@columbia.edu

------------------------------------------------------------------------

*NEW YORK CITY REGION, MEDICAL INFORMATICS ACTIVITIES*

*University at Stony Brook Medical Center: T*he Medical Informatics
Department is responsible for Academic Instruction and Information
Technology Training within the University Hospital & Medical
Center/Health Sciences Center. Our department works in conjunction with
the HSC Library staff to provide training for Medical Students and
technical support for the Learning Center's computer lab and classroom.
In addition, Medical Informatics is developing Computer Aided
Instruction (CAI) and the following projects: 1.Computer skills
training for Medical Students. 2.Medical Student Handbook 3. Implement
training for Nurses in conjunction with the Term to PC program.
4.Develop computer literacy classes for clinicians and residents. 5.
CrossCurrents Forum - an open forum for faculty, staff and students of
the Health Sciences Center and University Hospital providing informal
seminars on the intersection of technology with education and research.

* *An Open Discussion on Improving the Status of Medical Informatics
Teaching, Research and Service in New York State*
* *(use the e-mail form at the bottom of this page to mail your
comments to Don Parsons).*
* *Telemedicine (video-consulting) is proving very effective for
health care of closed institutions*
* *The forgotten Rural New York State. *The rural population of New
York State exceeds the total population of a number of smaller
states. A shortage of doctors (especially for family practice) in
rural areas is not improving. There is little help from managed
care since these organizations cannot be profitable in low-density
populations. Rural telemedicine networks are now active around
Albany (Albany Medical College), Cooperstown (Bassett Healthcare)
and Buffalo (University at Buffalo Health Sciences and Erie
County). Several penal and mental health institutions are using
video-consulting to reduce the costs of taking inmates to medical
centers.
* * In Nursing homes:* The Eddy nursing home group and 20 other
home groups and hospitals are involved in a $300, 000 computer
networking project funded by New York State. The network will
coordinate services, medicines, and other requirements of the
clients or residents (Times Union Feb 7, 1996).

**** To include your own activities send e-mail to Don Parsons using the
e-mail form at the end of this page.****
------------------------------------------------------------------------

*SELECTED PUBLIC HEALTH WEB SITES*

* *French Communicable Disease Network*(FCDN)
.* * France-wide volunteer
General Practitioners (the sentinel network) submit every Friday
an Electronic Data Interchange (EDI) form indicating the week's
notifiable conditions. The data is automatically gathered from
the forms and the weekly statstics calculated. Summaries are
returned electronically to all health units and also published in
a weekly bulletin (Bulletin Epidemiologique Hebdomadaire). The
notification of epidemics is the fastest achieved anywhere.
Results are in the form of charts and movies showing the changes
in incidences week by week or month by month. This site :
is in both French
and English and has links to most other notification summary URLs
of other countries. See: Parsons DF, Garnerin P, Flahault A. ,
Gotham IJ. 1996. Status of Electronic Reporting of Notifiable
Conditions in the United States and Europe. */TelemedicineJournal
/*2(4): 273-284.
* *The World Health Organization (WHO)* international public health
data is available at:
http://www.who.ch/programmes/WHOProgrammes.html
.
* *CDC Information Network for Public Health Officials (INPHO):*
The state health department provides a Web site that can be
accessed by all county and state public health practitioners.
Eventually, these Web sites will be interlinked nationwide.
Summaries for the 12 sites in Florida, Georgia, Illinois, Indiana,
Michigan, New York, North Carolina, Oregon, Rhode Island ,
Washington, and West Virginia are available at
http://www.cdc.gov/inpho/inpho.htm

* *CDC Morbidity and Mortality Weekly Reports (MMWR). *To obtain the
full, Acrobat (*.pdf) graphics version go to :
http://www.cdc.gov/Publications/SubscriptionServices/MMWR/ .
Select the date of the MMWR *.pdf file. You can obtain the free
Acrobat pdf software from this site.

*SELECTED MEDICAL INFORMATICS SITES*

*a). Computer Assisted Instruction (CAI)*

* *HTML Lecture Courses. *Detailed instructions for producing
hypertext lecture courses for teaching over the Web. From the
Computer Science Department of the University of British Columbia,
Canada. See: http://homebrew.cs.ubc.ca/webct/
.
* *Continuing Medical Education for Physicians (CME) on the Internet:*

* *The Interactive Patient: *(Marshall University School of
Medicine) http://medicus.marshall.edu/medicus.htm The physician
works up the presented patient interactively and requests some
tests, x-rays, etc. A diagnosis and a treatment plan are then
suggested by the user. After completing the first case the
physician can enroll for CME credits.
* *Interesting Cases*: seen at the Mass. General Hospital.
http://emergency.mgh.harvard.edu/webicc.htm
* The *Medical Education Network *of Loyola University:
http://www.meddean.luc.edu/lumen/MedEd/ .
* T*he Virtual Medical Center*: multimedia medic al courses:
http://www-sci.lib.uci.edu/~martindale/Medical.html
.
* I*ndex of Medical Image Resources*:
http://www.crs4.it/~france/MEDICAL/institutions.html
.

* *b). Broad Medical Informatics Resources*.

* *MedWeb: *A very large collection of medical informatics
applications and resources. Emory University medical centers were
pioneers in Unix based Hospital Information Systems and large
scale use of Computer-based Patient Records (CPR):
http://www.gen.emory.edu/medweb/medweb.informatics.html.
* *The Hardin Meta Directory *of Internet medical informatics:
http://www.arcade.uiowa.edu/hardin-www/md.html
.
* *Current Medical Informatics Research Training Institutional
Grantees: *Harvard/Tufts/NE Medical Center, Yale Center for
Medical Informatics, Columbia University, University of
Pittsburgh, Duke university, University of Minnesota Health
Sciences Center, University of Missouri, Rice University/Baylor
College of Medicine, Oregon Health Sciences University, Stanford
University School of Medicine, Regenstrief Institute, University
of Utah.
* *Free medical literature searches over the Internet:
*http://www.nnlm.nlm.nih.gov/ Free
MEDLINE available through Internet Grateful Med and PubMed.
1-800-338-7657. Internet Grateful Med V2.3.2 offers 11
databases. In addition to MEDLINE, HealthSTAR, PREMEDLINE, and
AIDSLINE, this version of Internet Grateful Med (IGM) offers free
access to AIDSDRUGS, AIDSTRIALS, DIRLINE, HISTLINE, HSRPROJ,
OLDMEDLINE, and SDILINE. When first invoked, Internet Grateful Med
is set to search in MEDLINE®. Select the "Search Other Files"
action on the Search Screen to change from MEDLINE to one of the
other databases accessible through IGM. Also gives access to
*Loansome Do*c and Clinical Alerts. IGM can map user terms through
NLM's Unified Medical Language System (UMLS) Metathesaurus to help
users create, submit and refine on-line searches. Internet
Grateful Med Development Team National Library of Medicine 8600
Rockville Pike Bethesda, MD 20894 USA or access@nlm.nih.gov.
* *Free medical literature searches via Physicians on Line: *If you
are an MD and hava a DEA number you can access all the databases
free using local phone numbers. The ads on the bottom one inch of
the screen explain why a DEA is needed. You can also purchase
low-cost, general Internet access from POL. 1-800 332-0009

* *c). Sources for Grants in Medical Informatics*
* *d). Computer Know-how for Telemedicine*
* * Organizing distributed networksiciml17
*
* *Handbook for Use of Free Unix (Linux and Solaris) on a PC
*iciml18
* * Tips on buying a computer iciml19
*
* *Solaris8 (Sparc and Intel) Command Summary click here
*

------------------------------------------------------------------------

* e-mail: dfp10@wadsworth.org. . Owner, Moderator, and Publisher of
hspnet-l@health.state.ny.us Discussion of Interhospital Networks
(Design and Use).
* Tel: (518) 474-7047. . Fax: 474-8590 To send e-mail to D. Parsons
clickHERE
* Department of Health, Empire State Plaza, Box 509, Albany,
NY12201-0509. Research-Physician III. [Also :Assistant Professor
Biometry and Statisics, Albany School of Public Health, State
University of New York at Albany, East Campus, One University
Place, Room 150, Rensselaer, NY 12144-3456].

End of MI Home Page. DFP

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