AIM: minds, morals, medicine

Abstract

Kazem Sadegh-Zadeh’s Handbook of Analytic Philosophy of Medicine does (among many other things) a wonderful job of introducing to the reader the idea of engaging soft computing theoretical foundations and techniques in dealing with clinical reasoning, diagnosis and representation in medical expert systems. Though massive and encyclopedic may it be, a good handbook must eschew the nitty-gritty details and the finest subtleties of implementation in order to give a cohesive and clear general view of the topic at hand. As an added bonus, this puts the interested reader in the right mindset: looking forward for a more technical analysis of what has just been hinted. Apart from revering Sadegh-Zadeh’s work for its notable qualities, this talk has two more targets in sight: - an historical recount of how fuzzy logic got into the frame in AIIM: I will briefly discuss some of the prototypical reasoning systems for medical problems, and how an extension to fuzzy logic came natural, and will move up to today’s cutting edge research to show that such extension is still actul, and the debate around it alive and kicking; - a compact analysis of the competitive advantages in using fuzzy methodologies in AIIM through examples, using data culled from the literature and some general inference. In harmony with one of the Handbook aims, this is a basic talk and requires only some knowledge of basic fuzzy logic: some may find it tedious and too basic for their tastes and knowledge, some may expect a more philosophically oriented approach. I hope the talk will be engaging enough to stimulate a rich discussion, and that it will give for fuzzy logic in AIIM at least a glimpse of an answer to the childlike question, “Yes, but, how does it work?”.