Folckers, Jörg and Möbus, Claus and Schröder, Olaf and Thole, Heinz-Jürgen (1996) An Intelligent Problem Solving Environment for Designing Explanation Models and for Diagnostic Reasoning in Probabilistic Domains. In: Intelligent Tutoring Systems. Lecture Notes in Computer Science (1086). Springer, Berlin, pp. 353-362.

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MEDICUS is an Intelligent Problem Solving Environment (IPSE) currently under development. It is designed to support i) the construction of explanation models, and ii) the training of diagnostic reasoning and hypotheses testing in domains of complex, fragile, and uncertain knowledge. MEDICUS is currently developed and applied in the epidemiological fields of environmentally caused diseases and human genetics. Uncertainty is handled by the Bayesian network approach. Thus the modelling task for the learner consists of creating a Bayesian network for the problem at hand. He / she may test hypotheses about the model, and the system provides help. This differs from existing reasoning systems based on Bayesian networks, i.e. in medical domains, which contain a built-in knowledge base that may be used but not created or modified by the learner. For supporting diagnostic reasoning, MEDICUS proposes diagnostic hypotheses and examinations. This will be extended to support learners' acquisition and training of diagnostic strategies.

Item Type: Book Section
Uncontrolled Keywords: MEDICUS, Intelligent Problem Solving Environment, IPSE, explanation models, diagnostic reasoning, diagnostic hypotheses testing, epidemiological fields of environmentally caused diseases and human genetics, Bayesian network approach, medical domains,
Subjects: Generalities, computers, information > Computer science, internet
Philosophy and psychology > Psychology
Divisions: School of Computing Science, Business Administration, Economics and Law > Department of Computing Science
Date Deposited: 29 Sep 2015 09:27
Last Modified: 29 Sep 2015 09:27
URN: urn:nbn:de:gbv:715-oops-22476
DOI: 10.13140/2.1.4013.3448

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