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

被引:2
|
作者
Bu, Xusong [1 ]
Zhang, Mingxia [2 ]
Zhang, Zhan [1 ]
Zhang, Qin [1 ,3 ]
机构
[1] Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
[2] Capital Med Univ, Otorhinolaryngol Head & Neck Surg, Xuan Wu Hosp, Beijing 100053, Peoples R China
[3] Tsinghua Univ, Inst Nucl & New Energy Technol, Beijing 100084, Peoples R China
关键词
causality; probability graph; sore throat; computer-aided diagnoses; KNOWLEDGE REPRESENTATION; DECISION-MAKING; DISEASE;
D O I
10.3390/diagnostics13071219
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Dynamic uncertain causality graph for computer-aided general clinical diagnoses with nasal obstruction as an illustration
    Qin Zhang
    Xusong Bu
    Mingxia Zhang
    Zhan Zhang
    Jie Hu
    [J]. Artificial Intelligence Review, 2021, 54 : 27 - 61
  • [2] Dynamic uncertain causality graph for computer-aided general clinical diagnoses with nasal obstruction as an illustration
    Zhang, Qin
    Bu, Xusong
    Zhang, Mingxia
    Zhang, Zhan
    Hu, Jie
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2021, 54 (01) : 27 - 61
  • [3] Differential disease diagnoses of epistaxis based on dynamic uncertain causality graph
    Bu, Xusong
    Zhang, Mingxia
    Zhang, Zhan
    Zhang, Qin
    [J]. EUROPEAN ARCHIVES OF OTO-RHINO-LARYNGOLOGY, 2023, 280 (04) : 1731 - 1740
  • [4] Differential disease diagnoses of epistaxis based on dynamic uncertain causality graph
    Xusong Bu
    Mingxia Zhang
    Zhan Zhang
    Qin Zhang
    [J]. European Archives of Oto-Rhino-Laryngology, 2023, 280 : 1731 - 1740
  • [5] COMPUTER-AIDED DIAGNOSES - INTRODUCTION
    LINDBERG, G
    [J]. SCANDINAVIAN JOURNAL OF GASTROENTEROLOGY, 1987, 22 : 151 - 151
  • [6] Dynamic Uncertain Causality Graph Applied to Dynamic Fault Diagnoses and Predictions With Negative Feedbacks
    Zhang, Qin
    Zhang, Zhan
    [J]. IEEE TRANSACTIONS ON RELIABILITY, 2016, 65 (02) : 1030 - 1044
  • [7] Dynamic Uncertain Causality Graph Applied to Dynamic Fault Diagnoses of Large and Complex Systems
    Zhang, Qin
    Geng, Shichao
    [J]. IEEE TRANSACTIONS ON RELIABILITY, 2015, 64 (03) : 910 - 927
  • [8] COMPUTER-AIDED CODIFICATION OF MEDICAL DIAGNOSES
    YANEZ, A
    CASTILLO, M
    JAQUE, J
    SOTO, F
    STIPO, J
    [J]. REVISTA MEDICA DE CHILE, 1994, 122 (07) : 825 - 829
  • [9] Bond graph based automated modeling for computer-aided design of dynamic systems
    Wu, Zhaohong
    [J]. JOURNAL OF MECHANICAL DESIGN, 2008, 130 (04)
  • [10] DYNAMIC FAULT TREE ANALYSIS BASED ON DYNAMIC UNCERTAIN CAUSALITY GRAPH
    Zhou, Zhenxu
    Dong, Chunling
    Zhang, Qin
    [J]. PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON NUCLEAR ENGINEERING, 2018, VOL 2, 2018,