A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

Journal: Artificial intelligence in medicine

Published Date: Aug 14, 2015

Abstract

OBJECTIVE: Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones.

Authors

Shaker El-Sappagh

Department of Mathematics, College of Science, King Saud University, PO 2455, Riyadh, Saudi Arabia.
Mohammed Elmogy

Information Technology Department, Faculty of Computers & Information, Mansoura University, PO 35516, Mansoura, Egypt. Electronic address: melmogy@mans.edu.eg.
A M Riad

Information Systems Department, Faculty of Computers & Information, Mansoura University, PO 35516, Mansoura, Egypt.

Keywords

Algorithms Artificial Intelligence Biological Ontologies Diabetes Mellitus Diagnosis, Computer-Assisted Fuzzy Logic Humans Information Storage and Retrieval Semantics Vocabulary, Controlled

External Resources

View on PubMed Access via DOI PubMed (26303105)

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

Abstract

Authors

Keywords

External Resources

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