Towards a Machine-Understandable Model Representing the Medical Decision

Badr Merad; Khaled Belkadi

doi:10.15866/iremos.v13i3.18695

Towards a Machine-Understandable Model Representing the Medical Decision

Badr Merad^(1*), Khaled Belkadi⁽²⁾

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/iremos.v13i3.18695

Abstract

The aim of this paper is to represent the medical decision in an understandable machine format. This representation is made possible by exploiting the powerful expressivity of semantic web languages. A major obstacle in modeling a medical decision is the frequent lack of evidence; it is usually based on the intuition and expertise of clinical practitioners. Therefore, Evidence-Based Medicine is a real solution to this problem. It is a medical approach created to make medicine an evidence-based science, like mathematics and physics. The result of this work is an OWL ontology presented in the Visual Notation for OWL Ontologies. This ontology represents the new format called Ontological Medical Decision Format and models medical decisions using an evidence-based approach. Unlike related works and in addition to being machine understandable, the proposed format allows a global representation of an evidence-based decision and enables Clinical Decision Support Systems to reach proven and justified decisions. The ontology development and evaluation process is also detailed.
Copyright © 2020 Praise Worthy Prize - All rights reserved.

Keywords

Clinical Decision Support Systems; Clinical Model; Evidence Based Medicine; Knowledge Representation; Ontology; Semantic Web

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