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

作者：

Highlights：

• Propose a fuzzy ontology based semantic-CBR framework.

• Propose a novel OWL2 fuzzy case-base ontology.

• Propose a fuzzy semantic case retrieval algorithm using an SNOMED CT fragment.

• Implement the fuzzy KI-CBR system using diabetes diagnosis as a case study.

• Combine fuzzy logic and ontology semantics in CBR enhances the CBR accuracy.

摘要

•Propose a fuzzy ontology based semantic-CBR framework.•Propose a novel OWL2 fuzzy case-base ontology.•Propose a fuzzy semantic case retrieval algorithm using an SNOMED CT fragment.•Implement the fuzzy KI-CBR system using diabetes diagnosis as a case study.•Combine fuzzy logic and ontology semantics in CBR enhances the CBR accuracy.

论文关键词：Case-based reasoning,Knowledge based system,Fuzzy ontology,Semantic retrieval,Diabetes diagnosis,Standard SNOMED CT terminology

论文评审过程：Received 30 October 2014, Revised 2 June 2015, Accepted 5 August 2015, Available online 14 August 2015, Version of Record 14 November 2015.

论文官网地址：https://doi.org/10.1016/j.artmed.2015.08.003