A theoretical approach to artificial intelligence systems in medicine.
The various theoretical models of disease, the nosology which is accepted by the medical community and the prevalent logic of diagnosis determine both the medical approach as well as the development of the relevant technology including the structure and function of the A.I. systems involved. A.I. systems in medicine, in addition to the specific parameters which enable them to reach a diagnostic and/or therapeutic proposal, entail implicitly theoretical assumptions and socio-cultural attitudes which prejudice the orientation and the final outcome of the procedure. The various models -causal, probabilistic, case-based etc. -are critically examined and their ethical and methodological limitations are brought to light. The lack of a self-consistent theoretical framework in medicine, the multi-faceted character of the human organism as well as the non-explicit nature of the theoretical assumptions involved in A.I. systems restrict them to the role of decision supporting "instruments" rather than regarding them as decision making "devices". This supporting role and, especially, the important function which A.I. systems should have in the structure, the methods and the content of medical education underscore the need of further research in the theoretical aspects and the actual development of such systems.
Technological Educational Institution of Athens, Medical Instrumentation Technology Department, Greece.
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Spyropoulos
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Papagounos
D001185:Artificial Intelligence; D003658:Decision Making, Computer-Assisted; D003662:Decision Theory; D006801:Humans; D007257:Information Theory; D008492:Medical Informatics Computing