AI-driven fall risk prediction in inpatients: Development, validation, and comparative evaluation

AI-driven fall risk prediction in inpatients: Development, validation, and comparative evaluation

Background & Aim: Falls among hospitalized patients pose severe consequences, necessitating accurate risk prediction. Traditional assessment tools rely on cross-sectional data and lack dynamic analysis, limiting clinical applicability. This study developed an AI-based fall risk prediction model...

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Bibliographic Details
Main Authors: Chia-Lun Lo, Chia-En Liu, Hsiao Yun Chang, Chiu-Hsiang Wu
Format: Article
Language:English
Published: Tehran University of Medical Sciences 2025-03-01
Series:Nursing Practice Today
Subjects:
falls; fall risk assessment comparison; hospitalized patients; supervised learning technology; nursing assessment; decision support system
Online Access:https://npt.tums.ac.ir/index.php/npt/article/view/3374
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https://npt.tums.ac.ir/index.php/npt/article/view/3374

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