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Artificial Intelligence in Medicine: Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, AIMDM'99, Aalborg, Denmark, June 20-24, 1999, Proceedings / Edition 1
     

Artificial Intelligence in Medicine: Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, AIMDM'99, Aalborg, Denmark, June 20-24, 1999, Proceedings / Edition 1

by Werner Horn, Yuval Shahar, Greger Lindberg, Steen Andreassen, Jeremy Wyatt
 

ISBN-10: 354066162X

ISBN-13: 9783540661627

Pub. Date: 07/20/1999

Publisher: Springer Berlin Heidelberg

The European Societies for Arti cial Intelligence in Medicine (AIME) and M- ical Decision Making (ESMDM) were both established in 1986.A major activity of both these societies has been a series of international conferences, held bi- nially over the last 13 years. In the year 1999 the two societies organized a joint conference for the r st time. It took place from

Overview

The European Societies for Arti cial Intelligence in Medicine (AIME) and M- ical Decision Making (ESMDM) were both established in 1986.A major activity of both these societies has been a series of international conferences, held bi- nially over the last 13 years. In the year 1999 the two societies organized a joint conference for the r st time. It took place from June 20{24th, 1999 in Aalborg, Denmark. This \Joint European Conference on Arti cial Intelligence in Medicine and Medical Decision Making (AIMDM’99)" was the seventh conference for each of thetwosocieties.ThisconferencefollowstheAIMEconferencesheldinMarseilles (1987), London (1989), Maastricht (1991), Munich (1993), Pavia (1995), and Grenoble(1997).PreviousESMDMconferenceshavebeenheldinLeiden(1986), Copenhagen (1988), Glasgow (1990), Marburg (1992), Lille (1994), and Torino (1996). The AIMDM conference is the major forum for the presentation and d- cussion of new ideas in the areas of Arti cial Intelligence and Medical Decision Making in Medicine. This ful lls the aims of both societies. The aims of AIME are to foster fundamental and applied researchin the applicationof Arti cial - telligence (AI) techniques to medicalcareandmedicalresearch,andto providea forum for reporting signi cant results achieved. ESMDM’s aims are to promote research and training in medical decision-making, and to provide a forum for circulating ideas and programs of related interest. In the AIMDM’99 conference announcement, authors were encouraged to submit original contributions to the development of theory, techniques, and - plications of both AI in medicine (AIM) and medical decision making (MDM).

Product Details

ISBN-13:
9783540661627
Publisher:
Springer Berlin Heidelberg
Publication date:
07/20/1999
Series:
Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence Series , #1620
Edition description:
1999
Pages:
462
Product dimensions:
6.10(w) x 9.25(h) x 0.36(d)

Table of Contents

Keynote Lectures.- From Clinical Guidelines to Decision Support.- Artificial Intelligence for Building Learning Health Care Organizations.- Timing Is Everything: Temporal Reasoning and Temporal Data Maintenance in Medicine.- Machine Learning for Data Mining in Medicine.- Guidelines and Prools.- Guidelines-Based Workflow Systems.- Enhancing Clinical Practice Guideline Compliance by Involving Physicians in the Decision Process.- Application of Therapeutic Prools: A Tool to Manage Medical Knowledge.- Decision Support Systems, Knowledge-Based Systems, Cooperative Systems.- From Description to Decision: Towards a Decision Support Training System for MR Radiology of the Brain.- Internet-Based Decision-Support Server for Acute Abdominal Pain.- Multi-modal Reasoning in Diabetic Patient Management.- Experiences with Case-Based Reasoning Methods and Prototypes for Medical Knowledge-Based Systems.- Exploting Social Reasoning of Open Multi-agent Systems to Enahnce Cooperation in Hospitals.- Influence Diagrams for Neonatal Jaundice Management.- Electronic Drug Prescribing and Administration - Bedside Medical Decision Making.- Neonatal Ventilation Tutor (VIE-NVT), a Teaching Program for the Mechanical Ventilation of Newborn Infants.- A Life-Cycle Based Authorisation Expert Database System.- A Decision-Support System for the Identification, Staging, and Functional Evaluation of Liver Diseases (HEPASCORE).- Model-Based Systems.- A Model-Based Approach for Learning to Identify Cardiac Arrhythmias.- A Model-Based System for Pacemaker Reprogramming.- Integrating Deep Biomedical Models into Medical Decision Support Systems: An Interval Constraint Approach.- Neural Networks, Causal Probabilistic Networks.- A Decision Theoretic Approach to Empirical Treatment of Bacteraemia Originating from the Urinary Tract.- An ECG Ischemic Detection System Based on Self-Organizing Maps and a Sigmoid Function Pre-processing Stage.- Neural Network Recognition of Otoneurological Vertigo Diseases with Comparison of Some Other Classification Methods.- A Comparison of Linear and Non-linear Classifiers for the Detection of Coronary Artery Disease in Stress-ECG.- The Case-Based Neural Network Model and Its Use in Medical Expert Systems.- Knowledge Representation.- A Medical Ontology Library That Integrates the UMLS Metathesaurus™.- The Use of the UMLS Knowledge Sources for the Design of a Domain Specific Ontology: A Practical Experience in Blood Transfusion.- Representing Knowledge Levels in Clinical Guidelines.- Temporal Reasoning.- Intelligent Analysis of Clinical Time Series by Combining Structural Filtering and Temporal Abstractions.- Knowledge-Based Event Detection in Complex Time Series Data.- Abstracting Steady Qualitative Descriptions over Time from Noisy, High-Frequency Data.- Visualization Techniques for Time-Oriented, Skeletal Plans in Medical Therapy Planning.- Visualizing Temporal Clinical Data on the WWW.- Machine Learning.- Machine Learning in Stepwise Diagnostic Process.- Refinement of Neuro-psychological Tests for Dementia Screening in a Cross Cultural Population Using Machine Learning.- The Analysis of Head Injury Data Using Decision Tree Techniques.- Machine Learning for Survival Analysis: A Case Study on Recurrence of Prostate Cancer.- ICU Patient State Characterization Using Machine Learning in a Time Series Framework.- Diagnostic Rules of Increased Reliability for Critical Medical Applications.- Machine Learning Inspired Approaches to Combine Standard Medical Measures at an Intensive Care Unit?.- A Screening Technique for Prostate Cancer by Hair Chemical Analysis and Artificial Intelligence.- Natural Language Processing.- A Conversational Model for Health Promotion on the World Wide Web.- Types of Knowledge Required to Personalise Smoking Cessation Letters.- Small Is Beautiful — Compact Semantics for Medical Language Processing.- Speech Driven Natural Language Understanding for Hands-Busy Recording of Clinical Information.- Automatic Acquisition of Morphological Knowledge for Medical Language Processing.- Image Processing and Computer Aided Design.- A Multi-agent System for MRI Brain Segmentation.- Modelling Blood Vessels of the Eye with Parametric L-Systems Using Evolutionary Algorithms.- Animating Medical and Safety Knowledge.- Active Shape Models for Customised Prosthesis Design.

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