基质辅助激光解吸电离飞行时间质谱平台结合机器学习建立快速鉴定耐甲氧西林金黄色葡萄球菌模型。
MALDI-TOF MS platform combined with machine learning to establish a model for rapid identification of methicillin-resistant Staphylococcus aureus.
机构信息
Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei Province, China.
Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, 430060, Hubei Province, China.
出版信息
J Microbiol Methods. 2021 Jan;180:106109. doi: 10.1016/j.mimet.2020.106109. Epub 2020 Nov 30.
MALDI-TOF MS is an effective potential tool to distinguish between MSSA and MRSA. By combining the ClinProTools3.0 software and manual grouping intervention, we proposed a model optimization method for the first time. The cross validation of the model increased from 95.82% to 96.68%, and the accuracy of the model increased from 88.89% to 91.98%. Finally, we reported nine characteristic peaks of rapid detection of MRSA.
基质辅助激光解吸电离飞行时间质谱（MALDI-TOF MS）是一种有效的潜在工具，可用于区分 MSSA 和 MRSA。通过结合 ClinProTools3.0 软件和手动分组干预，我们首次提出了一种模型优化方法。模型的交叉验证率从 95.82%提高到 96.68%，模型的准确性从 88.89%提高到 91.98%。最后，我们报告了快速检测 MRSA 的九个特征峰。
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