Intelligent analysis of laboratory equipment testing data based on BERT
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Yanbin Zhang
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Limin Du
Abstract
Review of laboratory test data is a management focus for compliance laboratories. Using BERT-based intelligent analysis to analyze the laboratory instrument test data can assist laboratory testing personnel to quickly and accurately obtain the target data. This paper, with high-performance liquid chromatography (HPLC) as an example, applies big data technology and machine learning algorithm to the intelligent analysis and application of instrument test data by reading the output files in combination with the historical data of laboratory management system and business system, to realize the automatic acquisition of instrument test data, which reduces the laboratory labor cost, improves the laboratory test efficiency, optimizes the laboratory test management, and improves the quality control level.
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Research ethics: This article does not contain any studies with human participants performed by any of the authors.
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Author contributions: Yanbin Zhang, Dan Liu, Yang Su is responsible for designing the framework, analyzing the performance, validating the results, and writing the article. Limin Du, Xiaoyu Ge, Xinsheng Gong, and Jinshun Zhou is responsible for collecting the information required for the framework, provision of software, critical review, and administering the process.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: Authors do not have any conflicts.
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Research funding: Authors did not receive any funding.
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Data availability: No datasets were generated or analyzed during the current study.
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