Artificial intelligence-integrated multimodal data-assisted magnetic resonance imaging for neoadjuvant chemoradiotherapy decision-making in cT1-2N0 rectal cancer

Figure 2 Schematic of Clinical, Hematologic, Oncopathologic, and Radiomic Decision machine-learning model construction and validation. A-C: They delineate the high-throughput radiomics feature extraction pipeline embedded within the Clinical, Hematologic, Oncopathologic, and Radiomic Decision framework; D: It illustrates the rigorous preprocessing of multidimensional clinical variables; E: It summarizes the comparative benchmarking of candidate models and the subsequent SHapley Additive exPlanations-driven post-hoc interpretability analysis. AUC: Area under the curve; DWI: Diffusion weighted imaging; GBM: Gradient boosting machine; KNN: K-nearest neighbors; LASSO: Least absolute shrinkage and selection operator; ROC: Receiver operating characteristic; ROI: Regions of interest; SVM: Support vector machine; 3D: Three-dimensional.