Modeling a Smart Teleradiology: Decision Support System based on Ontology

Abstract

Increasingly, hospitals are producing information related to additional examinations for reasons of in-depth investigations or diagnoses. Medical imaging plays an essential role in medical action, mainly for diagnosis, therapeutic planning, intraoperative navigation, postoperative monitoring, and biomedical research. From the perspective of Universal Health Coverage, teleradiology is one of the solutions to the lack of radiologist practitioners in certain territories. Given the situation of the health system in developing countries and in particular in DR Congo, we therefore aim to contribute by providing a solution under a project related to teleradiology. The system designed to make a link between clinical information, data extracted from images, and the radiological ontology for decision-making based on semi-supervised machine learning. This article presents the theoretical foundations of the study and highlights the implementation of our radiology ontology called Smart Ontology of Radiology (SORad).