A large language model for delirium prediction in the intensive care unit using structured electronic health records.

ABSTRACT: Delirium is an acute syndrome characterized by fluctuating attention, cognitive impairment, and severe disorganization of behavior, which has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection can enable timely interventions and improved health outcomes. While artificial intelligence (AI) models have shown great potential for ICU delirium prediction using structured electronic health records (EHR), most studies have either not leveraged state-of-the-art AI models, been limited to single-center cohorts, or relied on small datasets for development and validation. In this study, we introduce DeLLiriuM, a novel LLM-based delirium prediction model that utilizes EHR data from the first 24 hours of ICU admission to estimate a patient's risk of developing

SUBMITTER: Contreras M 

PROVIDER: S-EPMC12592510 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature