The process consists of four key components: (1) Data Preprocessing standardization and labeling of the training dataset, (2) Feature Engineering derivation of relevant features for robust glioma drug response prediction, (3) Training Module a comprehensive process involving initial training, feature reduction, and performance assessment for individual predictor development, and (4) Downstream Applications functionalities such as drug response predictions and microenvironment interpretations.
