Cancer adjuvant chemotherapy prediction model for non-small cell lung cancer - Alanni, Russul; Hou, Jingyu; Azzawi, Hasseeb; Xiang, Yong (IET systems biology, 2019)
Keywords: ACT classification; ACT information; ACT treatment; adjuvant chemotherapy; Algorithms; Bayes methods; Bayes Theorem; biochemistry; cancer; cancer ACT prediction model; cancer recurrence; cancer treatment; Carcinoma, Non-Small-Cell Lung - drug therapy; Carcinoma, Non-Small-Cell Lung - genetics; cellular biophysics; Chemotherapy, Adjuvant; conventional methods; decision tree; decision trees; Gene Expression Regulation, Neoplastic - drug effects; general regression neural network; genetics; gene‐expression programming algorithm; Humans; integrated microarray datasets; lung; Lung Neoplasms - drug therapy; Lung Neoplasms - genetics; medical computing; microarray gene‐expression datasets; microarray gene‐expression technology; Models, Statistical; naive Bayes; neural nets; nonsmall cell lung cancer; NSCLC treatment; NSCLC‐related prognostic genes; regression analysis; representative models; Research Article; support vector machine; support vector machines; surgery; surgery resection; survival time; Treatment Outcome; adjuvant chemotherapy; cancer treatment; cellular biophysics; integrated microarray datasets; regression analysis; ACT classification; representative models; NSCLC-related prognostic genes; decision tree; genetics; surgery resection; microarray gene-expression datasets; microarray gene-expression technology; NSCLC treatment; support vector machines; nonsmall cell lung cancer; cancer ACT prediction model; lung; support vector machine; survival time; conventional methods; ACT information; cancer recurrence; decision trees; biochemistry; naive Bayes; cancer; Bayes methods; general regression neural network; gene-expression programming algorithm; medical computing; neural nets; surgery; ACT treatment