title: INKBLOT: a neurological diagnostic decision support system integrating causal and anatomical knowledge.
abstract: As an initial step in the diagnostic process, human neurologists often use anatomical localization to constrain the set of diagnostic hypotheses 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 generates a set of hypothetical localizations relative to a coordinate system of nested cubes and then uses these localization(s) to explain the manifestations. We trace the reasoning mechanism utilized by INKBLOT-1 for a particular set of symptoms and show how INKBLOT-1 is able to generate novel hypotheses that explain the observed manifestations. In doing this, INKBLOT-1 demonstrates capabilities not demonstrated by previously described systems.
authors.affiliation: Center for Biomedical Informatics, University of Pittsburgh, PA 15213, USA.
authors.forename: G
authors.initials: G
authors.lastname: Citro
authors.forename: G
authors.initials: G
authors.lastname: Banks
authors.forename: G
authors.initials: G
authors.lastname: Cooper
mesh_terms: D001185:Artificial Intelligence; D003663:Decision Trees; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D009422:Nervous System Diseases / Q000175:diagnosis*; D009462:Neurology / Q000379:methods*