A Novel Multivariable Prediction Model for Predicting [Outcome] Using a Neural Network Approach

This document is a TRIPOD checklist referencing a study that developed and validated a multivariable prediction model using a neural network. Internal validation employed four-fold cross-validation. Predictors included clinical features and radiomic features. Sample size determination and handling of missing data are described in the referenced manuscript sections. Statistical analysis details include how predictors were handled, the model-building procedures, and performance assessment measures. No model updating (e.g., recalibration) was performed during validation.

Performance results are reported in the Results (e.g., Tables 1–4 and supplementary tables), but specific numerical outcomes are not provided in this checklist.