Title: SEPHYRES 2: applying semantic-pseudo-fuzzy methods in medical diagnostic ontologies

Authors: Ali Sanaeifar; Mahmood Tara; Ahmad Faraahi; Bibimasoumeh Mir Mousavi; Mitra Ahadi; Ali Bahari

Addresses: Payam-e-Noor University of Tehran (PNU), P.O. Box 19395-3697, Tehran, Iran ' Department of Medical Informatics, Mashhad University of Medical Science (MUMS), Mashhad, Iran ' Department of Computer Engineering and Information Technology, Payam-e-Noor University of Tehran (PNU), Tehran, PO.BOX 19395-3697, Iran ' Women, Gender, and Sexuality Studies Department, Oregon State University (OSU), Corvallis, Oregon, USA ' Department of Internal Medicine, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran ' Endoscopic & Minimally Invasive Surgery Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

Abstract: To date, ontology-based medical diagnostic systems have not incorporated complete descriptions of diseases and their semantic relations with signs and symptoms. In SEPHYRES 1, a pain-focused-only solution was proposed which applied not only general semantic reasoners, but also weight spreading techniques. Proceeding the research, we developed the SEPHYRES knowledge base to address all signs, symptoms and complex relations, including similar terms, terms with the variant generality level, composed terms, terms which include several other terms based on medical diagnostic criteria. The evaluation outcomes, in terms used in patient's descriptive history in both of the MEDSCAPE and PubMed case studies, showed that the recall amount of system-oriented evaluation was about 90% provided that just top ten results were considered. Furthermore, the Wilcoxon signed-ranked test between SEPHYRES 2 and the best symptom checker, Isabel engine power, showed that the SEPHYRES 2 significantly improved the matching process of the patient's disease profiles.

Keywords: computer assisted diagnosis; clinical decision support; knowledge modelling; computer assisted decision making.

DOI: 10.1504/IJMEI.2018.093366

International Journal of Medical Engineering and Informatics, 2018 Vol.10 No.3, pp.265 - 278

Received: 03 Apr 2017
Accepted: 05 Apr 2017
Published online: 25 Jul 2018 *

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