Transatlantic transferability and replicability of machine-learning algorithms to predict mental health crises.

ABSTRACT: Transferring and replicating predictive algorithms across healthcare systems constitutes a unique yet crucial challenge that needs to be addressed to enable the widespread adoption of machine learning in healthcare. In this study, we explored the impact of important differences across healthcare systems and the associated Electronic Health Records (EHRs) on machine-learning algorithms to predict mental health crises, up to 28 days in advance. We evaluated both the transferability and replicability of such machine learning models, and for this purpose, we trained six models using features and methods developed on EHR data from the Birmingham and Solihull Mental Health NHS Foundation Trust in the UK. These machine learning models were then used to predict the mental health crises of 2907 pat

SUBMITTER: Guerreiro J 

PROVIDER: S-EPMC11384787 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature