Research on quality management technology of fully automatic blood cell analyzer based on device characteristics
10.3969/j.issn.1672-8270.2024.10.023
- VernacularTitle:基于设备特性的全自动血球分析仪质量管理研究
- Author:
Qiong KONG
1
;
Yan JIANG
;
Ling TANG
;
Hui LI
Author Information
1. 新疆医科大学第一附属医院医学检验中心 乌鲁木齐 830000
- Keywords:
Equipment characteristics;
Fully automatic blood cell analyzer;
Quality management;
Artificial intelligence
- From:
China Medical Equipment
2024;21(10):123-128
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a quality prediction and diagnosis model for fully automatic blood cell analyzers based on equipment characteristics,and to explore its application value in dynamic quality management and control of fully automatic blood cell analyzers.Methods:Based on the characteristics of the equipment,the quality prediction and diagnosis model for automatic blood cell analyzer was constructed by using the Long Short Term Memory(LSTM)model and Softmax classifier and Adam optimization algorithm,and 18 equipment characteristics parameters were designed as input variables to predict and diagnose 10 common quality problems.The data of five automatic blood cell analyzers in clinical use in the Laboratory Center of the First Affiliated Hospital of Xinjiang Medical University from 2021 to 2022 were selected as samples for model training and testing,and the prediction accuracy and diagnostic accuracy of the model were evaluated,and the auxiliary effect of quality management of five automatic blood cell analyzers from January to June 2023 was observed with the model output results.The performance of the quality prediction and diagnosis model was evaluated by accuracy and precision,and the reduction in the average number of weekly failures before and after the model-assisted quality management of the fully automatic blood cell analyzer was compared.Results:The model was applied to the prediction diagnosis of five devices,and the prediction accuracy rates were 97.5%、95.9%、96.3%、95.3%and 95.2%,respectively,and there was no significant difference in the prediction and diagnosis accuracy of the five devices(P>0.05).The diagnostic accuracy was 92.6%、89.7%、91.1%、92.4%,and 91.1%,respectively,with no statistically significant difference(P>0.05).The predictive diagnostic accuracy of the five devices was 92.6%,89.7%,91.1%,92.4%and 91.1%,respectively,and there was no significant difference in the predictive diagnostic accuracy of the five devices(P>0.05).After applying the model to assist the quality management control of five devices,the average weekly failure rate decreased by 67.35%,68.36%,69.72%,68.97%,and 67.47%,respectively.Conclusion:The quality prediction and diagnosis model of the fully automatic blood cell analyzer based on equipment characteristics can accurately predict equipment quality problems according to the equipment characteristic values,correctly diagnose the causes of quality problems and propose corresponding treatment measures.It can be applied to equipment quality management and control to effectively reduce the failure rate and is suitable for different equipment.
