Decision Under Uncertainty in Diagnosis

2013/03/27 by Charles I. Kalme, Kalme, Charles I.
Biochemistry, Genetics and Molecular Biology · Computer Science · #AI-based Problem Solving and Planning #Artificial Intelligence (cs.AI) #Biomedical Text Mining and Ontologies #FOS: Computer and information sciences #Rough Sets and Fuzzy Logic #cs.AI

paper · pdf · doi:10.48550/arxiv.1304.3094

Appears in Proceedings of the Second Conference on Uncertainty in Artificial Intelligence (UAI1986)

arxiv created 2013/03/27 · openalex publication_date 2013/03/27 · arxiv updated 2013/04/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper describes the incorporation of uncertainty in diagnostic reasoning based on the set covering model of Reggia et. al. extended to what in the Artificial Intelligence dichotomy between deep and compiled (shallow, surface) knowledge based diagnosis may be viewed as the generic form at the compiled end of the spectrum. A major undercurrent in this is advocating the need for a strong underlying model and an integrated set of support tools for carrying such a model in order to deal with uncertainty.

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