https://www.selleckchem.com/pr....oducts/z-yvad-fmk.ht
For performance evaluation and validation, the proposed methods were applied to independent gene expression datasets. Among the four ML algorithms evaluated, the Support Vector Machine algorithm was able to classify breast cancer more accurately into triple negative and non-triple negative breast cancer and had less misclassification errors than the other three algorithms evaluated. The prediction results show that ML algorithms are efficient and can be used for classification of breast cancer into triple negative and non-triple nega
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