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For major STs, the ML models generated by GA-KNN algorithms attained highest cross validation values in comparison to SNN and QC algorithms. GA-KNN models of ST10, ST17, and ST12/ST19 had good diagnostic efficiency, with high sensitivity (95-100%), specificity (91.46%-99.23%), accuracy (92.79-99.29%), positive prediction value (PPV, 80%-92.68%), negative prediction value (NPV, 94.32%-99.23%). Peak markers were firstly identified for ST10 (m/z 6250, 3125, 6891) and ST17 strains (m/z 2956, 5912, 7735, 5218). Statistical models for rapid GB
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