https://www.selleckchem.com/products/dw71177.html
914, 95% confidence interval, 4.430-17.934, P less then 0.001). By using this model, the enrolled patients were classified into sensitive (SE) and insensitive (INS) groups. The pCR rates between the SE and INS groups were highly different (42.3% vs.7.6%, P less then 0.001). The sensitivity and specificity of this prediction model were 84.5% and 62.0%. CONCLUSIONS Instead of whole transcriptome-based technologies, panel gene expression with tens of essential genes implemented in a machine learning model has predictive potential for chemo
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