Acid Base Disorders
Acute Renal Failure
Angle Closure Glaucoma
artificial intelligence techniques
Caput Medusae
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Causal Graph
Chronic Angle Closure Glaucoma
Chronic Primary Angle Closure Glaucoma
Ciliary Block
clinical decision support
Common Duct Stone
computational medicine
computer-assisted clinical diagnosis
computing techniques
diagnostic algorithms
Diagnostic Task
Differential Diagnostic Procedures
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Glaucoma Program
health care system
Hemolytic Anemia
Hepatic Vein Obstruction
Ill Structured
Ill Structured Problems
Infectious Disease Diagnosis
Intermediate Hypotheses
Knowledge Acquisition
knowledge representation in healthcare
medical expert systems
Mixed Connective Tissue Disease
Patient Specific Model
Patient's Illness
Planning Links
Portal Hypertension
Primary Angle Closure Glaucoma
rule-based reasoning
Thyroid Dysfunction
Product details
- ISBN 9780367022211
- Weight: 610g
- Dimensions: 143 x 225mm
- Publication Date: 07 Jun 2019
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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This book introduces the field of artificial intelligence in medicine, a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care. An introductory chapter describes the historical and technical foundations of the work and provides an overview of the current state of the art and research directions. The authors then describe four prototype computer programs that tackle difficult clinical problems in a manner similar to that of an expert physician. The programs presented are internist, a diagnostic aid that combines a large database of disease/manifestation associations with techniques for problem formulation; expert and the Glaucoma Program which use physiological models for the diagnosis and treatment of eye disease; mycin, a rule-based program for diagnosis and therapy selection for infectious diseases; and the Digitalis Therapy Advisor, which aids the physician in prescribing the right dose of the drug digitalis and also explains its actions.
Peter Szolovits is an associate professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. A specialist in artificial intelligence (AI) with an emphasis on medical applications, he is currently concerned with fundamental issues of representation and reasoning, including protocol analysis to discover how clinicians reason about probability and causality, and with programs which model human expert performance in some areas of medical diagnosis and care.
