Artificial Intelligence in Medicine

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Acid Base Disorders
Acute Renal Failure
Age Group_Uncategorized
Age Group_Uncategorized
Angle Closure Glaucoma
artificial intelligence techniques
automatic-update
B01=Peter Szolovits
Caput Medusae
Category1=Non-Fiction
Category=JHB
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
COP=United Kingdom
Delivery_Pre-order
diagnostic algorithms
Diagnostic Task
Differential Diagnostic Procedures
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eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
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
Language_English
medical expert systems
Mixed Connective Tissue Disease
PA=Temporarily unavailable
Patient Specific Model
Patient's Illness
Planning Links
Portal Hypertension
Price_€20 to €50
Primary Angle Closure Glaucoma
PS=Active
rule-based reasoning
softlaunch
Thyroid Dysfunction

Product details

  • ISBN 9780367172084
  • Weight: 312g
  • Dimensions: 143 x 225mm
  • Publication Date: 07 Dec 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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This book presents the research efforts in the U. S. in artificial intelligence application techniques to medical decision making. It has grown out of a Symposium on Artificial Intelligence in Medicine presented at the 1979 Annual Meeting of the American Association for the Advancement of Science.

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.