MALDI-TOF MS platform combined with machine learning to establish a model for rapid identification of methicillin-resistant Staphylococcus aureus

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.