Fig. 2: Schematic diagram illustrating the two-strategy evaluation framework implemented in our study. | npj Digital Medicine

Fig. 2: Schematic diagram illustrating the two-strategy evaluation framework implemented in our study.

From: Predicting response to neoadjuvant chemotherapy in muscle-invasive bladder cancer via interpretable multimodal deep learning

Fig. 2

The dataset is initially split into an 80% discovery subset and a 20% hold-out test set, utilizing stratified random sampling at the patient level to ensure consistent data distribution among the different splits. Within the discovery subset, stratified 5-fold cross-validation is applied for model development and optimal parameter selection. The hold-out test set is then used to conduct an unbiased evaluation of the final model, assessing its performance on previously unseen data.

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