A model-based method for computer-aided medical decision-making

Sholom M. Weiss, Casimir A. Kulikowski, Saul Amarel, Aran Safir

Research output: Contribution to journalArticlepeer-review

261 Scopus citations


A general method of computer-assisted medical decision-making has been developed based on causal-associational network (CASNET) models of disease. A CASNET model consists of three main components: observations of a patient, pathophysiological states, and disease classifications. As observations are recorded, they are associated with the appropriate states. States are causally related, forming a network that summarizes the mechanisms of disease. Patterns of states in the network are linked to individual disease classifications. Recommendations for broad classes of treatment are triggered by the appropriate diagnostic classes. Strategies of specific treatment selection are guided by the individual pattern of observations and diagnostic conclusions. This approach has been applied in a consultation program for the diagnosis and treatment of the glaucomas.

Original languageEnglish (US)
Pages (from-to)145-172
Number of pages28
JournalArtificial Intelligence
Issue number1-2
StatePublished - Aug 1978

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence


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