Journal of clinical medicine
Comparison of Internal Validation Strategies for Estimating Machine Learning Model Performance in One-Year Mortality Prediction in Hepatocellular Carcinoma
Par Kucukakcali Z, Akbulut S et Sarici KB.
Contenu en anglais
Résumé
Background
Machine learning (ML) performance estimates in hepatocellular carcinoma (HCC) may depend on internal validation strategy, especially in small datasets.
Aim
To develop models for one-year mortality prediction and compare performance, calibration, decision-analytic performance, and uncertainty estimates using a conventional train-test split and nested cross-validation (nCV).