A CONSTRAINT REPRESENTATION AND EXPLANATION FACILITY FOR RENAL PHYSIOLOGY
I. J Ashbell · 1984
Current research in Artificial Intelligence has yielded computer programs which have potential to augment the physician''s ability to diagnose illness. The medical diagnoses programs of the first generation contain medical facts representing associations between diseases and findings. A most important step is the development of computer programs that have models of physiological processes and have the ability to derive physiological justifications of observed signs and symptoms. In this thesis, a program which models the casual mechanism underlying a subset of human physiology is unveiled. We shall begin with a discussion of the relevant AI techniques used: envisionment, qualitative reasoning, propagation of constraints and grey boxes. To tie together these methodologies, the concept of explanation boxes is introduced. The rest of the thesis is devoted to the presentation of an explanation box network which is able to represent the physiological pertaining to three syndromes of renal physiology