Causal Models for Medical Artificial Intelligence
A large number of expert systems have been developed using artificial intelligence (AI) techniques to assist in medical diagnosis and treatment.1,2 Most of these systems involve “surface models” of their domains rather than “causal models” of the underlying physiologic and pathophysiologic processes. Such a surface model links sets of patient findings with different diseases to assist diagnosis or defines the clinical conditions for which particular treatments are recommended.
KeywordsCholesterol Filtration Covariance Germinal Glaucoma
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