Clinical Decision Support System for the Respiratory Diseases Diagnosis

Abstract

The existing decision support systems used in healthcare for analyzing and processing medical data is considered in the article, their functionality is discussed. The solution for developing decision support systems to diagnose bronchopulmonary diseases, allowing to establish the patient’s primary diagnosis treatments based on the integration of intelligent information processing, machine learning, pattern recognition, and extraction knowledge is proposed. The scheme of the proposed clinical decision support system for the diagnosis of respiratory diseases is discussed. Developing the clinical decision support system with the list of proposed capabilities will, on one hand, significantly improve the quality of medical care, since it reduces risks of human factors due to the use of computer-based information processing, and, on the other hand, increase the level of digitalization in medical institutions as well as their economic efficiency. Keywords—clinical decision support system, data processing, machine learning, pattern recognition