This paper is in the following e-collection/theme issue:

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Natural Language Processing (791) Clinical Information and Decision Making (1612) Electronic Health Records (1163)

Published on in Vol 10, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37913, first published .
Impact of a Clinical Text–Based Fall Prediction Model on Preventing Extended Hospital Stays for Elderly Inpatients: Model Development and Performance Evaluation

Impact of a Clinical Text–Based Fall Prediction Model on Preventing Extended Hospital Stays for Elderly Inpatients: Model Development and Performance Evaluation

Impact of a Clinical Text–Based Fall Prediction Model on Preventing Extended Hospital Stays for Elderly Inpatients: Model Development and Performance Evaluation

Authors of this article:

Yoshimasa Kawazoe1 Author Orcid Image ;   Kiminori Shimamoto1 Author Orcid Image ;   Daisaku Shibata1 Author Orcid Image ;   Emiko Shinohara1 Author Orcid Image ;   Hideaki Kawaguchi2, 3 Author Orcid Image ;   Tomotaka Yamamoto4 Author Orcid Image
Article Authors Cited by (6) Tweetations (3) Metrics

Journals

  1. Trinh V, Zhang S, Kovoor J, Gupta A, Chan W, Gilbert T, Bacchi S. The use of natural language processing in detecting and predicting falls within the healthcare setting: a systematic review. International Journal for Quality in Health Care 2023;35(4) View
  2. Lee M, Seo B, Kim M. Time-Varying Hazard of Patient Falls in Hospital: A Retrospective Case–Control Study. Healthcare 2023;11(15):2194 View
  3. Peng Y, Wang Y, Wen Z, Xiang H, Guo L, Su L, He Y, Pang H, Zhou P, Zhan X. Deep learning and machine learning predictive models for neurological function after interventional embolization of intracranial aneurysms. Frontiers in Neurology 2024;15 View
  4. Saito C, Nakatani E, Sasaki H, E Katsuki N, Tago M, Harada K. Predictive Factors and the Predictive Scoring System for Falls in Acute Care Inpatients: Retrospective Cohort Study. JMIR Human Factors 2025;12:e58073 View
  5. Mao A, Su J, Ren M, Chen S, Zhang H. Risk prediction models for falls in hospitalized older patients: a systematic review and meta-analysis. BMC Geriatrics 2025;25(1) View
  6. Peng J, Xu D, Hu P, Sheng J, Huang T. A deep learning–based method to predict the length of stay for patients with traumatic fall injuries in support of physicians' clinical decisions and patient management. Decision Support Systems 2025;191:114411 View