Computer-Aided Diagnoses for Sore Throat Based on Dynamic Uncertain Causality Graph

Author:

Bu Xusong1,Zhang Mingxia2,Zhang Zhan1,Zhang Qin13

Affiliation:

1. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

2. Otorhinolaryngology Head & Neck Surgery, Xuan Wu Hospital of the Capital Medical University, Beijing 100053, China

3. Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China

Abstract

The causes of sore throat are complex. It can be caused by diseases of the pharynx, adjacent organs of the pharynx, or even systemic diseases. Therefore, a lack of medical knowledge and experience may cause misdiagnoses or missed diagnoses in sore throat diagnoses, especially for general practitioners in primary hospitals. This study aims to develop a computer-aided diagnostic system to assist clinicians in the differential diagnoses of sore throat. The computer-aided system is developed based on the Dynamic Uncertain Causality Graph (DUCG) theory. We cooperated with medical specialists to establish a sore throat DUCG model as the diagnostic knowledge base. The construction of the model integrates epidemiological data, knowledge, and clinical experience of medical specialists. The chain reasoning algorithm of the DUCG is used for the differential diagnoses of sore throat. The system can diagnose 27 sore throat-related diseases. The model builder initially tests it with 81 cases, and all cases are correctly diagnosed. Then the system is verified by the third-party hospital, and the diagnostic accuracy is 98%. Now, the system has been applied in hundreds of primary hospitals in Jiaozhou City, China, and the degree of recognition for doctors to the diagnostic results of the system is more than 99.9%. It is feasible to use DUCG for the differential diagnoses of sore throat, which can assist primary doctors in clinical diagnoses and the diagnostic results are acceptable to clinicians.

Funder

Institute for Guo Qiang, Tsinghua University

Publisher

MDPI AG

Subject

Clinical Biochemistry

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