Application and prospect of machine learning in identification and prediction of medical equipment
10.3969/j.issn.1672-8270.2025.01.025
- VernacularTitle:机器学习在医疗设备故障识别与预测中的应用与展望
- Author:
Xiaoyu CHEN
1
;
Zihong WANG
;
Haitao GUO
;
Xiaolong HUANG
;
Wenqin CHEN
Author Information
1. 陆军军医大学第一附属医院医学工程科 重庆 400038
- Publication Type:Journal Article
- Keywords:
Medical device;
Fault identification and fault prediction;
Machine learning;
Neural network;
Deep learning
- From:
China Medical Equipment
2025;22(1):143-149
- CountryChina
- Language:Chinese
-
Abstract:
The conventional identification and prediction for failures of medical equipment mainly depend on experience and knowledge of manager for equipment,which are not able to be quantified and have lower efficiency. Therefore,it is obvious that the prediction for the failure of medical equipment is not accurate. With the technical development of computer and machine learning,the conventional identification and prediction that depend on experiences can deal with characteristics of failures through machine learning method to improve efficiency,which are hopeful in filling the gap of discipline about the identification and prediction for failures of medical equipment. This article summarized the application situation of machine learning in identifying and predicting failures of the medical equipment and the similarly electric equipment at home and abroad. Based on the key technique of identification and prediction,this article proposed suggestion about corresponding design architecture. According to the characteristics of the failure of medical equipment,this article summarized a series of information about algorithms of various machine learning in scene and accurate rate of identification and prediction,so as to provide references for relevant research of this field.
