INKBLOT - A NEUROLOGICAL DIAGNOSTIC DECISION-SUPPORT SYSTEM INTEGRATING CAUSAL AND ANATOMICAL KNOWLEDGE

As an initial step in the diagnostic process, human neurologists often use anatomical localization to constrain the set of diagnostic hypoth eses deserving further consideration. We describe an automated system, INKBLOT-1, which uses anatomical localization in much the same way as human neurologists. Given a set of manifestations, INKBLOT-1 generate s a set of hypothetical localizations relative to a coordinate system of nested cubes and then uses these localization(s) to explain the man ifestations. We trace the reasoning mechanism utilized by INKBLOT-1 fo r a particular set of symptoms and show how INKBLOT-1 is able to gener ate novel hypotheses that explain the observed manifestations. In doin g this, INKBLOT-1 demonstrates capabilities not demonstrated by previo usly described systems. (C) 1997 Elsevier Science B.V.