{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["2"],"submitter":["Wilimitis D"],"pubmed_abstract":["Cross-validation remains a popular means of developing and validating artificial intelligence for health care. Numerous subtypes of cross-validation exist. Although tutorials on this validation strategy have been published and some with applied examples, we present here a practical tutorial comparing multiple forms of cross-validation using a widely accessible, real-world electronic health care data set: Medical Information Mart for Intensive Care-III (MIMIC-III). This tutorial explored methods such as K-fold cross-validation and nested cross-validation, highlighting their advantages and disadvantages across 2 common predictive modeling use cases: classification (mortality) and regression (length of stay). We aimed to provide readers with reproducible notebooks and best practices for model"],"journal":["JMIR AI"],"pagination":["e49023"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11041453"],"repository":["biostudies-literature"],"pubmed_title":["Practical Considerations and Applied Examples of Cross-Validation for Model Development and Evaluation in Health Care: Tutorial."],"pmcid":["PMC11041453"],"pubmed_authors":["Wilimitis D","Walsh CG"],"additional_accession":[]},"is_claimable":false,"name":"Practical Considerations and Applied Examples of Cross-Validation for Model Development and Evaluation in Health Care: Tutorial.","description":"Cross-validation remains a popular means of developing and validating artificial intelligence for health care. Numerous subtypes of cross-validation exist. Although tutorials on this validation strategy have been published and some with applied examples, we present here a practical tutorial comparing multiple forms of cross-validation using a widely accessible, real-world electronic health care data set: Medical Information Mart for Intensive Care-III (MIMIC-III). This tutorial explored methods such as K-fold cross-validation and nested cross-validation, highlighting their advantages and disadvantages across 2 common predictive modeling use cases: classification (mortality) and regression (length of stay). We aimed to provide readers with reproducible notebooks and best practices for model","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Dec","modification":"2026-06-01T21:55:41.836Z","creation":"2025-04-06T03:15:37.299Z"},"accession":"S-EPMC11041453","cross_references":{"pubmed":["38875530"],"doi":["10.2196/49023"]}}