Study on decision tree-based optimization algorithm for medical equipment fault diagnosis
10.19745/j.1003-8868.2025091
- VernacularTitle:基于决策树的医疗设备故障诊断优化算法研究
- Author:
Zi-jian YANG
1
;
Ke-chao ZHAO
1
;
Jing-chang LU
1
;
Hong-tao XING
1
Author Information
1. 陆军军医大学士官学校医技保障系,石家庄 050081
- Publication Type:Journal Article
- Keywords:
medical equipment;
fault judgement;
fault diagnosis;
decision tree;
logical function simplification;
greedy algorithm
- From:
Chinese Medical Equipment Journal
2025;46(5):78-83
- CountryChina
- Language:Chinese
-
Abstract:
Objective To propose a decision tree-based optimization algorithm to shorten the time spent and to improve the decision-making efficiency for medical device fault diagnosis.Methods Firstly,a binarized fault state space for medical equipment was constructed;secondly,the binarized fault state space was simplified with logical functions;finally,a greedy algorithm was applied to iterative judgment to build a decision tree for medical device fault diagnosis.The algorithm proposed was compared with the greedy algorithm,Gini coefficient method and random forest algorithm in terms of the result accuracy and time cost and the influences of fault probability distribution and time-consuming differences for the algorithms.A case study on gastric lavage machine fault diagnosis was conducted to demonstrate the algorithm.Results The algorithm proposed behaved better than the greedy algorithm,Gini coefficient method and random forest algorithm in lowered time cost and result accuracy.However,the algorithm showed a decrease in accuracy for the logarithmic distribution of the detection method's time consumption,and it was not sensitive to the changes in the failure rate distribution.The gastric lavage machine case study demonstrated that the algorithm was functionally similar to an experienced engineer.Conclusion The proposed algorithm with overall perspective effectively enhances fault judgment efficiency and facilitates rapid diagnostic decision-making in medical equipment maintenance.[Chinese Medical Equipment Journal,2025,46(5):78-83]
