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Machine Learning List Vol. 5 No. 16
Machine Learning List: Vol. 5 No. 16
Friday, August 6, 1993
Contents:
Knowledge Discovery in Databases Workshop (KDD-93) Proceedings
POSITION AVAILABLE - STATISTICIAN
Recent Georgia Tech papers and tech reports available by FTP
Preprint Available: Random-Walk Learning in Neural Networks
CFP -- AIM'94 symposium
Call for papers Conference on Uncertainty in Artificial Intelligence
COMPUTATIONAL HEALTH (long)
The Machine Learning List is moderated. Contributions should be relevant to
the scientific study of machine learning. Mail contributions to ml@ics.uci.edu.
Mail requests to be added or deleted to ml-request@ics.uci.edu. Back issues
may be FTP'd from ics.uci.edu in pub/ml-list/V<X>/<N> or N.Z where X and N are
the volume and number of the issue; ID: anonymous PASSWORD: <your mail address>
----------------------------------------------------------------------
Date: Fri, 6 Aug 93 14:02:40 EDT
From: Gregory Piatetsky-Shapiro <gps0%eureka@gte.COM>
Subject: Knowledge Discovery in Databases Workshop (KDD-93) Proceedings
******** Knowledge Discovery in Databases (KDD-93) **************
Proceedings of this AAAI-93 Workshop
are now available as a AAAI technical report.
Knowledge Discovery is an area of common interest for researchers in
machine learning, statistics, intelligent databases, knowledge
acquisition, and expert systems, focusing on unifying themes such as
the use of domain knowledge, managing uncertainty, interactive
discovery, and transition from research to application.
This workshop brought together over 60 researchers from 10 countries.
28 selected papers are included in the proceedings.
Contents:
Part 1. Real World Applications (9 papers)
Part 2. Discovery of Dependencies and Models (8 papers)
Part 3. Integrated and Interactive Systems (6 papers)
Part 4. Database-Specific Techniques (3 papers)
Part 5. Discovery in Textual Documents (2 papers)
(send mail to gps@gte.com to get full contents)
____________________________________________________________
To order contact
Daphne Black
AAAI
445 Burgess Drive
Menlo Park, CA 94025-3496
Tel: 415-328-3123 e-mail: sem@aaai.org
Cost: $20 + shipping
Within the US and Canada (shipped by UPS): $3.50 for the first book,
and $1.00 for each additional book.
Outside of the US and Canada: $6.50 per book surface and $15.25 per
book airmail.
*Please allow 4-6 weeks for delivery.
California residents must pay 8.25% sales tax in addition to the
cost of shipping the reports.
------------------------------
From: Phil Goodman <goodman@unr.EDU>
Subject: POSITION AVAILABLE - STATISTICIAN
Date: Mon, 12 Jul 93 23:02:29 GMT
******************* Professional Position Announcement ******************
"STATISTICIAN for NEURAL NETWORK & REGRESSION DATABASE RESEARCH"
.- - - - - - - - - - - - - - OVERVIEW - - - - - - - - - - - - - - - - -.
| |
| THE LOCATION: |
| Nevada's Reno/Lake Tahoe region is an outstanding environment for |
| living, working, and raising a family. Winter skiing is world-class,|
| summer recreation includes many mountain and water sports, and |
| historical exploration and cultural opportunities abound. |
| |
| THE PROJECT: |
| The new CENTER FOR BIOMEDICAL MODELING RESEARCH recently received |
| federal funding to refine and apply a variety of artificial neural |
| network algorithms to large cardiovascular health care databases. |
| |
| THE CHALLENGE: |
| The predictive performance of neural nets will be compared to |
| advanced regression models. Other comparisons to be made include |
| handling of missing and noisy data, and selection of important |
| interactions among variables. |
| |
| THE JOB REQUIREMENT: |
| Masters-level or equivalent statistician with working knowledge |
| of the SAS statistical package and the UNIX operating system. |
| |
| THE SALARY : |
| Approximate starting annual salary: $42,000 + full benefits . |
| (actual salary will depend on experience and qualifications) |
._ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ .
POSITION: Research Statistics Coordinator for
NEURAL NETWORKS / HEALTH CARE DATABASE PROJECT
LOCATION: Center for Biomedical Modeling Research
Department of Internal Medicine
University of Nevada School of Medicine
Washoe Medical Center, Reno, Nevada
START DATE: September 1, 1993
CLOSING DATE: Open until filled.
DESCRIPTION: Duties include acquisition and translation of data
from multiple external national sources; data management and archiving;
performance of exploratory and advanced regression statistics;
performance of artificial neural network processing; participation
in scholarly research and publications.
QUALIFICATIONS: (1) M.S., M.A., M.P.H. or equivalent training in
statistics with experience in logistic and Cox regression analyses,
(2) ability to program in the SAS statistical language, and
(3) experience with UNIX computer operating systems.
Desirable but not mandatory are the abilities to use
(4) the S-PLUS data management system and (5) the C programming language.
SALARY: Commensurate with qualifications and experience.
(For example, with database experience, typical annual
salary would be approximately $42,000 + full benefits.)
APPLICATION: > Informal inquiry may be made to:
Phil Goodman, Director, Center for Biomedical Modeling Research
Internet: goodman@unr.edu Phone: 702-328-4867
> Formal consideration requires a letter of application,
vita, and names of three references sent to:
Philip Goodman, MD, MS
Director, Center for Biomedical Modeling Research
University of Nevada School of Medicine
Washoe Medical Center, Room H1-166
77 Pringle Way, Reno, NV 89520
The University of Nevada is an Equal Opportunity/Affirmative Action
employer and does not discriminate on the basis of race, color,
religion, sex, age, national origin, veteran's status or handicap
in any program it operates. University of Nevada employs only U.S.
citizens and aliens lawfully authorized to work in the United States.
************************************************************************
------------------------------
Date: Tue, 3 Aug 93 13:31:47 EDT
From: Ashwin Ram <ashwin@cc.gatech.EDU>
Subject: Recent Georgia Tech papers and tech reports available by FTP
Here is a list of AI/Cognitive Science titles recently added to the
ftp.cc.gatech.edu:/pub/ai electronic archive (see the ABSTRACTS file in this
directory for a complete list of titles, authors, abstracts, and publication
information):
<file>.ps.Z Title
___________ _____
er-93-01 Goal-Driven Learning: Fundamental Issues and Symposium Report
er-93-02 A New Perspective on Story Understanding
er-93-03 A Multistrategy Case-Based and Reinforcement Learning Approach
to Self-Improving Reactive Control Systems for Autonomous
Robotic Navigation
er-93-04 Creative Conceptual Change
er-93-05 Continuous Case-Based Reasoning
er-93-06 Computational Models of the Utility Problem and their
Application to a Utility Analysis of Case-Based Reasoning
er-93-07 Knowledge Compilation and Speedup Learning in Continuous Task
Domains
git-cc-92-02 A Theory of Questions and Question Asking
git-cc-92-03 Indexing, Elaboration and Refinement: Incremental Learning of
Explanatory Cases
git-cc-92-04 The Use of Explicit Goals for Knowledge to Guide Inference and
Learning
git-cc-92-19 Introspective Reasoning using Meta-Explanations for
Multistrategy Learning
git-cc-92-57 Case-Based Reactive Navigation: A Case-Based Method for On-Line
Selection and Adaptation of Reactive Control Parameters in
Autonomous Robotic Systems
git-cs-93-02 Introspective Multistrategy Learning
All files are retrievable using anonymous FTP from ftp.cc.gatech.edu
(130.207.3.245) from the directory /pub/ai. Login as anonymous and
enter your real name as the password. Use binary mode to download
compressed (.Z) files, uncompress the file, then print on any standard
Postscript printer. The archives are also accessible through WAIS and
ALEX; see the README file for more information.
__
Ashwin Ram <ashwin.ram@cc.gatech.edu>
Assistant Professor, College of Computing
Georgia Institute of Technology, Atlanta, Georgia 30332-0280
------------------------------
Date: Fri, 23 Jul 93 08:10:35 MDT
From: "Russell W. Anderson" <rwa@spine.lanl.GOV>
Subject: Preprint Available: Random-Walk Learning in Neural Networks
PREPRINT AVAILABLE:
"Biased Random-Walk Learning:
A Neurobiological Correlate to Trial-and-Error"
(In press: Progress in Neural Networks)
Russell W. Anderson
Los Alamos National Laboratory
Abstract:
Neural network models offer a theoretical testbed for
the study of learning at the cellular level.
The only experimentally verified learning rule,
Hebb's rule, is extremely limited in its ability
to train networks to perform complex tasks.
An identified cellular mechanism responsible for
Hebbian-type long-term potentiation, the NMDA receptor,
is highly versatile. Its function and efficacy are
modulated by a wide variety of compounds and conditions
and are likely to be directed by non-local phenomena.
Furthermore, it has been demonstrated that NMDA receptors
are not essential for some types of learning.
We have shown that another neural network learning
rule, the chemotaxis algorithm, is theoretically much more powerful
than Hebb's rule and is consistent with experimental data.
A biased random-walk in synaptic weight space is
a learning rule immanent in nervous activity and
may account for some types of learning __ notably the
acquisition of skilled movement.
__________________________________________
Electronic copy available, excluding 2 figures.
For hardcopies of the figures, please
contact me by email or slow mail.
To obtain a postscript copy:
%ftp mhc.lanl.gov
login: anonymous
password: <your email address>
ftp> cd pub
ftp> binary
ftp> get bias.ps.Z
ftp> quit
%uncompress bias.ps.Z
%lpr bias.ps
E-mail:
send request to rwa@temin.lanl.gov
Slow mail:
Russell Anderson
Theoretical Division (T-10)
MS K710
Los Alamos National Laboratory
Los Alamos, NM 87545
USA
(505) 667-9455
------------------------------
Date: Mon, 2 Aug 93 11:54:22 PDT
From: Serdar Uckun <uckun@hpp.stanford.EDU>
Subject: CFP -- AIM'94 symposium
Call for Papers
AAAI 1994 Spring Symposium:
Artificial Intelligence in Medicine: Interpreting Clinical Data
(March 21-23, 1994, Stanford University, Stanford, CA)
The deployment of on-line clinical databases, many supplanting the
traditional role of the paper patient chart, has increased rapidly over the
past decade. The consequent explosion in the quality and volume of
available clinical data, along with an ever more stringent medicolegal
obligation to remain aware of all implications of these data, has created a
substantial burden for the clinician. The challenge of providing intelligent
tools to help clinicians monitor patient clinical courses, forecast likely
prognoses, and discover new relational knowledge, is at least as large as
that generated by the knowledge explosion which motivated earlier efforts
in Artificial Intelligence in Medicine (AIM). Whereas many of the
pioneering programs worked on small data sets which were entered
interactively by knowledge engineers or clinicians, the current generation
of programs have to act on raw data, unfiltered and unmediated by human
beings. Interaction with human users typically only occurs on demand or on
detection of clinically significant events. The emphasis of this symposium
will be on methodologies that provide robust autonomous performance in
data-rich clinical environments ranging from busy outpatient practices to
operating rooms and intensive care units. Relevant topics include
intelligent alarming (including anticipation and prevention of adverse
clinical events), data abstraction, sensor validation, preliminary event
classification, therapy advice, critiquing, and assistance in the
establishment and execution of clinical treatment protocols. Detection of
temporal and geographical patterns of disease manifestations and machine
learning of clinical patterns are also of interest.
Organizing committee
Serdar Uckun, Co-chair (Stanford University)
Isaac Kohane, Co-chair (Harvard Medical School)
Enrico Coiera (Hewlett-Packard Laboratories/Bristol)
Ramesh Patil (USC/Information Sciences Institute)
Mario Stefanelli (Universita di Pavia)
Format
A large data sample will be made available to participants to serve as
training and test sets for various approaches to information management and
to provide a common domain of discourse. The sample will consist of two
data sets:
* A dense, high volume data set typical of a critical care environment.
This data set will consist of hemodynamic measurements, mechanical
ventilator settings, laboratory values including arterial blood gas
measurements, and treatment information covering a 12-hour period of a
patient with severe respiratory distress. Monitored parameters (10-15
channels of data) will be sampled and recorded at rates up to 1/10 Hz.
The data set will be annotated with other clinically relevant data,
physician's interpretations, and established diagnoses.
* A large number of sparse data sets representative of outpatient
environments. The data will include laboratory measurements, treatment
information, and physical findings on a large sample of patients (50 to
100 patients) taken from the same disorder population. Each patient record
will consist of several weeks' or months' worth of clinical information
sampled at irregular intervals. Most of the cases will be made available
to interested researchers to be used as training cases. For interested
parties, a small percentage of cases will be made available two weeks
prior to the symposium to be used as an optional testing set for various
approaches.
The data samples and accompanying clinical information will be available
via ftp or e-mail server around August 15, 1993. Please contact the
organizers at the addresses below for further information. The
data will also be made available on diskettes to participants who do not
have Internet access. It will be left to the discretion of the participants
to use any subset of these samples to help focus their approaches and
presentations. The data can also be used as test vehicles for their own
research and to create sample programs for demonstration at the symposium.
Participants do not have to use the data in order to participate. However,
the program committee will favor presentations which exploit the provided
data sets in their analyses.
Submission process
Potential participants are invited to submit abstracts no longer than
2 pages (< 1200 words) by October 15, 1993. The abstracts should outline
methodology and indicate, if applicable, how the provided data may be used
as a proof-of-principle for the discussed methodology. Electronic submissions
are encouraged. The abstracts may be sent to <aim-94@camis.stanford.edu>
in ASCII, RTF, or PostScript formats. Authors of accepted abstracts will
be asked to submit a working paper by January 31, 1994. They will also be
asked to prepare either a poster or an oral presentation.
Submissions by mail
Use this method ONLY IF you cannot submit an abstract electronically. Fax
submissions will not be accepted. Send 6 copies of the abstract to:
Serdar Uckun, MD, PhD
Co-chair, AIM-94
Knowledge Systems Laboratory
Stanford University
701 Welch Road, Bldg. C
Palo Alto, CA 94304
U.S.A.
Phone: [+1] (415) 723-1915
Calendar
Abstracts due: October 15, 1993
Notification of authors by: November 15, 1993
Working papers due: January 31, 1994
Spring Symposium: March 21-23, 1994
Information
For further information, please contact the co-chairs at the address above
or (preferably) via e-mail at:
<aim-94@camis.stanford.edu>
[Note: UCI will try to make copies of the databases available
at the UCI Repository of Machine Learning Databases]
------------------------------
Date: Fri, 30 Jul 1993 16:59:36 UTC
From: Ramon Lopez de Mantaras <mantaras@ceab.es>
Subject: call for papers
Tenth Annual Conference on
Uncertainty in Artificial Intelligence
July 29-31, 1994, Seattle, Washington
Reasoning under uncertainty is pervasive in all areas of Artificial
Intelligence. The Uncertainty in AI conference is the major forum for
advances in the theory and practice of reasoning under uncertainty.
We are seeking contributions both from researchers interested in
advancing the technology and from practitioners who are using
uncertainty techniques in applications.
The tenth annual Conference on Uncertainty in Artificial Intelligence
will be devoted to methods for reasoning under uncertainty as applied
to problems in artificial intelligence. The conference's scope covers
the full range of approaches to automated and interactive reasoning
and decision making under uncertainty, including both qualitative and
numeric methods.
We seek papers on fundamental theoretical issues, on representational
issues, on computational techniques and on applications of uncertain
reasoning, using traditional and alternative paradigms of uncertain
reasoning. Topics of interest include (but are not limited to):
Methods and Techniques
foundations of uncertainty concepts,
representation languages for uncertain knowledge,
knowledge acquisition,
construction of uncertainty models from data,
uncertainty in machine learning,
automated planning and acting,
uncertainty in ill-defined environments,
decision making under uncertainty,
algorithms for uncertain inference,
empirical studies of reasoning strategies,
pooling of uncertain evidence,
belief updating and inconsistency handling,
summarization of uncertain information, and
control of reasoning and real-time architectures.
Applications
Why was it necessary to represent uncertainty in your domain?
What kind of uncertainties does your application address?
Why did you decide to use your particular uncertainty formalism?
What theoretical problems, if any, did you encounter?
What practical problems did you encounter?
Did users of your system find the results or recommendations useful?
Did your system lead to improvements in reasoning
or decision making?
What methods were used to validate the effectiveness of the systems?
What did you learn about what was or was not effective in your domain?
Papers will be refereed for originality, significance, technical
soundness, and clarity of exposition. Application papers will be
judged according to criteria appropriate for application papers, such
as those related to the questions above. Papers may be accepted for
presentation in plenary or poster sessions. Some key applications
oriented work may be presented both in a plenary session and in a
poster session where more technical details can be discussed. All
accepted papers will be included in the published proceedings.
Outstanding student papers may be selected for special distinction.
Submission of Papers
Five copies of complete papers (hardcopy only) should be sent to one
of the Program Co-Chairs by February 1, 1994. The first page
should include a descriptive title, the names, addresses (regular mail
and email), and student status of all authors, a brief abstract, and
salient keywords or other topic indicators. To aid in finding
appropriate reviewers, the title, abstract and keywords should be
e-mailed to uai94@cs.ubc.ca. Acceptance notices will be sent by
March 31, 1994. Final camera-ready papers, incorporating reviewers'
suggestions, will be due approximately four weeks later. There will
be an eight-page limit on proceedings papers, with one extra page
available for a fee.
Program Co-Chairs (paper submissions):
Ramon L'opez de M'antaras
Artificial Intelligence Research Institute, CSIC
%Cami de Santa Barbara
17300 Blanes, Spain
Tel: +34-72-336101,
Fax: +34-72-337806
e-mail: mantaras@ceab.es
David Poole,
Department of Computer Science,
2366 Main Mall, Room 201,
University of British Columbia,
Vancouver, B.C., Canada V6T 1Z4
Tel: +1 (604) 822-6254,
Fax: +1 (604) 822-5485
email: poole@cs.ubc.ca
General Chair (conference inquiries):
David Heckerman
One Microsoft Way
Building 9S/1024
Redmond, WA 98052-6399
Tel: (206) 936-2662, Fax: (206) 644-1899
email: heckerma@microsoft.com
------------------------------
Date: Mon, 19 Jul 93 18:17:45 CDT
From: mwitten@hermes.chpc.utexas.EDU
Subject: COMPUTATIONAL HEALTH (long)
Preliminary Announcement
FIRST WORLD CONGRESS
ON COMPUTATIONAL MEDICINE, PUBLIC HEALTH AND
BIOTECHNOLOGY
24-28 April 1994
Hyatt Regency Hotel
Austin, Texas
1.0 CONFERENCE OVERVIEW: With increasing frequency,
computational sciences are being exploited as a means
with which to investigate biomedical processes at all
levels of complexity; from molecular to systemic to
demographic. Computational instruments are now used,
not only as exploratory tools but also as diagnostic
and prognostic tools. The appearance of high
performance computing environments has, to a great
extent, removed the problem of increasing the
biological reality of themathematical models. For the
first time in the history of the field, practical
biological reality is finally within the grasp of the
biomedical modeler. Mathematical complexity is no
longer as serious an issue as speeds of computation
are now of the order necessary to allow extremely
large and complex computational models to be analyzed.
Large memory machines are now routinely available.
Additionally, high speed, efficient, highly optimized
numerical algorithms are under constant development.
As these algorithms are understood and improved upon,
many of them are transferred from software
implementation to an implementation in the hardware
itself; thereby further enhancing the available
computational speed of current hardware. The purpose
of this congress is to bring together a
transdisciplinary group of researchers in medicine,
public health, computer science, mathematics, nursing,
veterinary medicine, ecology, allied health, as well
as numerous otherdisciplines, for the purposes of
examining the grand challenge problems of the next
decades. This will be a definitive meeting in that it
will be the first World Congress of its type and will
be held as a followup tothe very well received
Workshop On High Performance Computing In The Life
Sciences and Medicine held by the University of Texas
System Center For High Performance Computing in 1990.
Young scientists are encouraged to attend and to
present their work in this increasingly interesting
discipline. Funding is being solicited from NSF, NIH,
DOE, Darpa, EPA, and private foundations, as well as
other sources to assist in travel support and in the
offsetting of expenses for those unable to attend
otherwise. Papers, poster presentations, tutorials,
focussed topic workshops, birds of a feather groups,
demonstrations, and other suggestions are also
solicited.
2.0 CONFERENCE SCOPE AND TOPIC AREAS: The Congress
hasa broad scope. If you are not sure as to
whether or not your subject fits the Congress
scope, contact the conference organizers at one
of the addresses below.
Subject areas include but are not limited to:
*Visualization/Sonification
___ medical imaging
___ molecular visualization as a clinical
research tool
___ simulation visualization
___ microscopy
___ visualization as applied to problems
arising in computational molecular
biology and genetics or other non-traditional
disciplines
*Computational Molecular Biology and Genetics
___ computational ramifications of clinical
needs in the Human Genome, Plant Genome,
and Animal Genome Projects
___ computational and grand challenge problems in
molecular biology and genetics
___ algorithms and methodologies
___ issues of multiple datatype databases
*Computational Pharmacology, Pharmacodynamics,
Drug Design
*Computational Chemistry as Applied to Clinical Issues
*Computational Cell Biology, Physiology,
and Metabolism
___ Single cell metabolic models (red blood cell)
___ Cancer models
___ Transport models
___ Single cell interaction with external factors
models (laser, ultrasound, electrical stimulus)
*Computational Physiology and Metabolism
___ Renal System
___ Cardiovascular dynamics
___ Liver function
___ Pulmonary dynamics
___ Auditory function, coclear dynamics, hearing
___ Reproductive modeling: ovarian dynamics,
reproductive ecotoxicology, modeling the
hormonal cycle
___ Metabolic Databases and metabolic models
*Computational Demography, Epidemiology, and
Statistics/Biostatistics
___ Classical demographic, epidemiologic,
and biostatistical modeling
___ Modeling of the role of culture, poverty,
and other sociological issues as they
impact healthcare
*Computational Disease Modeling
___ AIDS
___ TB
___ Influenza
___ Statistical Population Genetics Of Disease
Processes
___ Other
*Computational Biofluids
___ Blood flow
___ Sperm dynamics
___ Modeling of arteriosclerosis and related
processes
*Computational Dentistry, Orthodontics, and
Prosthetics
*Computational Veterinary Medicine
___ Computational issues in modeling non-human
dynamics such as equine, feline, canine dynamics
(physiological/biomechanical)
*Computational Allied Health Sciences
___ Physical Therapy
___ Neuromusic Therapy
___ Resiratory Therapy
*Computational Radiology
___ Dose modeling
___ Treatment planning
*Computational Surgery
___ Simulation of surgical procedures in VR worlds
___ Surgical simulation as a precursor to surgical
intervention
*Computational Cardiology
*Computational Nursing
*Computational Models In Chiropractice
*Computational Neurobiology and Neurophysiology
___ Brain modeling
___ Single neuron models
___ Neural nets and clinical applications
___ Neurophysiological dynamics
___ Neurotransmitter modeling
___ Neurological disorder modeling (Alzheimers
Disease, for example)
*Computational Models of Psychiatric and Psychological
Processes
*Computational Biomechanics
___ Bone Modeling
___ Joint Modeling
*Computational Models of Non-tradional Medicine
___ Acupuncture
___ Other
*Computational Issues In Medical Instrumentation
Design and Simulation
___ Scanner Design
___ Optical Instrumentation
*Ethical issues arising in the use of computational
technology in medical diagnosis and simulation
*The role of alternate reality methodologies
and high performance environments in the medical and
public health disciplines
*Issues in the use of high performance computing
environments in the teaching of health science
curricula
*The role of high performance environments
for the handling of large medical datasets (high
performance storage environments, high performance
networking, high performance medical records
manipulation and management, metadata structures
and definitions)
*Federal and private support for transdisciplinary
research in computational medicine and public health
3.0 CONFERENCE COMMITTEE
*CONFERENCE CHAIR: Matthew Witten, UT System Center
For High Performance Computing, Austin, Texas
m.witten@chpc.utexas.edu
*CONFERENCE DIRECTORATE: Regina Monaco, Mt. Sinai
Medical Center * Dan Davison, University of Houston *
Chris Johnson, University of Utah * Lisa Fauci, Tulane
University * Daniel Zelterman, University of Minnesota
Minneapolis * James Hyman, Los Alamos National
Laboratory * Richard Hart, Tulane University * Dennis
Duke, SCRI-Florida State University * Sharon Meintz,
University of Nevada Los Vegas * Dean Sittig,
Vanderbilt University * Dick Tsur, UT System CHPC *
Dan Deerfield, Pittsburgh Supercomputing Center *
Istvan Gyori, Szeged University School of Medicine
Computing Center * Don Fussell, University of Texas at
Austin * Ken Goodman, University Of Miami School of
Medicine * Martin Hugh-Jones, Louisiana State
University * Stuart Zimmerman, MD Anderson Cancer
Research Center * John Wooley, DOE * Sylvia Spengler,
University of California Berkeley, Robert Blystone,
Trinity University
Additional conference directorate members are
being added and will be updated on the anonymous
ftp list as they agree.
4.0 CONTACTING THE CONFERENCE COMMITTEE: To contact
the congress organizers for any reason use any of the
following pathways:
ELECTRONIC MAIL - compmed94@chpc.utexas.edu
FAX (USA) - (512) 471-2445
PHONE (USA) - (512) 471-2472
GOPHER:log into the University of Texas System-CHPC
select the Computational Medicine and Allied Health
menu choice
ANONYMOUS FTP: ftp.chpc.utexas.edu
cd /pub/compmed94
POSTAL:
Compmed 1994
University of Texas System CHPC
Balcones Research Center, 1.154CMS
10100 Burnet Road
Austin, Texas 78758-4497
5.0 SUBMISSION PROCEDURES: Authors must submit 5
copies of a single-page 50-100 word abstract clearly
discussing the topic of their presentation. In
addition, authors must clearly state their choice of
poster, contributed paper, tutorial, exhibit, focussed
workshop or birds of a feather group along with a
discussion of their presentation. Abstracts will be
published as part of the preliminary conference
material. To notify the congress organizing committee
that you would like to participate and to be put on
the congress mailing list, please fill out and return
the form that follows this announcement. You may use
any of the contact methods above. If you wish to
organize a contributed paper session, tutorial
session,focussed workshop, or birds of a feather
group, please contact the conference director at
mwitten@chpc.utexas.edu
*CONFERENCE DEADLINES: The following deadlines should
be noted:
1 October 1993 - Notification of interest in
participation and/or intent
to organize a special session
1 November 1993 - Abstracts for talks/posters/
workshops/birds of a feather
sessions/demonstrations
15 January 1994 - Notification of acceptance of
abstract
15 February 1994 - Application for financial aid
6.0 CONFERENCE PRELIMINARY DETAILS AND ENVIRONMENT
LOCATION: Hyatt Regency Hotel, Austin, Texas, USA
DATES: 24-28 April 1994
The 1st World Congress On Computational Medicine,
Public Health, and Biotechnology will be held at the
Hyatt Regency Hotel, Austin, Texas located in
downtown Austin. The hotel is approximately 15 minutes
from Robert Meuller Airport. Austin, the state
capital, is renouned for its natural hill-country
beauty and an active cultural scence. Several hiking
and jogging trails are within walking distance of
the hotel, as well as opportunities for a variety of
aquatic sports. Live bands perform in various
nightclubs around the city and at night spots along
Sixth Street, offering a range of jazz, blues,
country/Western, reggae, swing, and rock music.
Day temperatures will be in the 80-90(degree F)
range and fairly humid. Exhibitor and vendor
presentations are also being planned.
7.0 CONFERENCE ENDORSEMENTS AND SPONSORSHIPS:
Numerous potential academic sponsors have been
contacted. Currently negotiations are underway
for sponsorship with SIAM, AMS, MAA, IEEE, FASEB, and
IMACS. Additionally AMA and ANA continuing medical
education support is beging sought. Information
will be updated regularly on the anonymous ftp
site for the conference (see above).
================== INTENT TO PARTICIPATE =============
First Name:
Middle Initial (if available):
Family Name:
Your Professional Title:
[ ]Dr.
[ ]Professor
[ ]Mr.
[ ]Mrs.
[ ]Ms.
[ ]Other:__________________
Office Phone (desk):
Office Phone (message):
Home/Evening Phone (for emergency contact):
Fax:
Electronic Mail (Bitnet):
Electronic Mail (Internet):
Postal Address:
Institution or Center:
Building Code:
Mail Stop:
Street Address1:
Street Address2:
City:
State:
Country:
Zip or Country Code:
Please list your three major interest areas:
Interest1:
Interest2:
Interest3:
=====================================================
------------------------------
End of ML-LIST (Digest format)
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