Ebook: AIME 91: Proceedings of the Third Conference on Artificial Intelligence in Medicine, Maastricht, June 24–27, 1991

This book contains 26 papers describing research in the do- main of Artificial Intelligence in Medicine. The papers are grouped around the following themes: Methodology, knowledge representation, clinical applications, modelling, uncertain- ty management, knowledge acquisition, and the user perspec- tive. The book gives an overview of the current state of AI in medicine research in Europe. It presents several techni- ques and methods that are likely to play an important role in future applications. In the section on clinical applica- tions not only existing systems are described, but results of evaluation studies are presented as well.

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This book contains 26 papers describing research in the do- main of Artificial Intelligence in Medicine. The papers are grouped around the following themes: Methodology, knowledge representation, clinical applications, modelling, uncertain- ty management, knowledge acquisition, and the user perspec- tive. The book gives an overview of the current state of AI in medicine research in Europe. It presents several techni- ques and methods that are likely to play an important role in future applications. In the section on clinical applica- tions not only existing systems are described, but results of evaluation studies are presented as well.

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This book contains 26 papers describing research in the do- main of Artificial Intelligence in Medicine. The papers are grouped around the following themes: Methodology, knowledge representation, clinical applications, modelling, uncertain- ty management, knowledge acquisition, and the user perspec- tive. The book gives an overview of the current state of AI in medicine research in Europe. It presents several techni- ques and methods that are likely to play an important role in future applications. In the section on clinical applica- tions not only existing systems are described, but results of evaluation studies are presented as well.
Content:
Front Matter....Pages I-VIII
Front Matter....Pages 1-1
Model-Based Image Segmentation: Methods and Applications....Pages 3-24
Real Versus Artificial Expertise: The Development of Cognitive Models of Clinical Reasoning....Pages 25-37
Front Matter....Pages 39-39
A Developmental Perspective on the Role of Biomedical Knowledge in Medical Problem Solving; Implications for AI....Pages 41-50
The role of domain models in maintaining consistency of large medical knowledge bases....Pages 51-71
Front Matter....Pages 72-81
A Framework for Causal Reasoning with a Functional Approach....Pages 83-83
Modelling and Knowledge (Re)presentation within HIOS+....Pages 85-94
Medical Knowledge Representation and Predictive Data Entry....Pages 95-104
Front Matter....Pages 105-116
A Connectionist Aid to the Early Diagnosis of Myocardial Infarction....Pages 117-117
Automation of Medical Audit in General Practice....Pages 119-128
An intelligent system for monitoring infections in heart transplant recipients....Pages 129-139
Measuring performance of a Bayesian decision support system for the diagnosis of rheumatic disorders....Pages 140-149
The Application of Distributed Artificial Intelligence to Medical Diagnosis....Pages 150-159
Knowledge Representation of Discharge Summaries....Pages 160-172
Front Matter....Pages 173-182
Dual Teleological Perspectives in Qualitative Circulatory Analysis....Pages 183-183
Physiological modelling using RL....Pages 185-197
Integrated use of causal and algebraic physiological models to support anaesthetists in decision making....Pages 198-210
Front Matter....Pages 211-223
Cytotoxic Chemotherapy Monitoring Using Stochastic Simulation on Graphical Models....Pages 225-225
A Model-Based Approach to Insulin Adjustment....Pages 227-238
A Blackboard Control Architecture for Therapy Planning....Pages 239-248
Front Matter....Pages 249-259
A comparative evaluation of three approaches to the acquisition of medical knowledge....Pages 261-261
A Knowledge Acquisition Tool for Medical Diagnostic Knowledge — Based Systems....Pages 263-272
Machine Learning in Data Rich Domains: Some Experiences from the KAVAS Project....Pages 273-282
Front Matter....Pages 283-293
Patient’s and Physician’s Opinion about Computer Expert Systems....Pages 295-295
Designing an Adaptive Interface for EPIAIM....Pages 297-305
CAP: A Critiquing Expert System for Medical Education....Pages 306-316
Back Matter....Pages 317-327
....Pages 329-332