Development and Validation of an Interpretable Machine Learning Model for Inpatient Fall Risk Using Electronic Health Record Data.

Background: Falls are the most common hospital-acquired adverse event, leading to extended hospitalization, loss of independence, disability, and premature death. Routine fall risk assessments are time-consuming, even with limited factors. An AI-derived fall prediction model can provide more compreh...

Descripción completa

Detalles Bibliográficos

Publicado en:	Nursing Reports Vol. 16; no. 8; pp. 283 - 306
Autores principales:	Mordiffi, Siti Zubaidah, Guo, Xiujuan, Goh, Mien Li, Ngiam, Kee Yuan, Wong, Neng Wei, Chua, Jenny, Furqan, Mohammad Shaheryar, Chew, Han Shi Jocelyn
Formato:	research tables/charts Journal Article
Publicado:	MDPI Aug2026
Acceso en línea:	Ver este registro en EBSCOhost