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

Falls Prevention in the Elderly (105) Artificial Intelligence (2249) Mobile Health (mhealth) (3564) mHealth for Telemedicine and Homecare (547) mHealth in a Clinical Setting (759) Nursing in a Long-Term Care Facility / Nursing Home for the Elderly (54)

Published on in Vol 7 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55681, first published .
Evaluating the Prognostic and Clinical Validity of the Fall Risk Score Derived From an AI-Based mHealth App for Fall Prevention: Retrospective Real-World Data Analysis

Evaluating the Prognostic and Clinical Validity of the Fall Risk Score Derived From an AI-Based mHealth App for Fall Prevention: Retrospective Real-World Data Analysis

Evaluating the Prognostic and Clinical Validity of the Fall Risk Score Derived From an AI-Based mHealth App for Fall Prevention: Retrospective Real-World Data Analysis

Authors of this article:

Sónia A Alves1 Author Orcid Image ;   Steffen Temme1 Author Orcid Image ;   Seyedamirhosein Motamedi1 Author Orcid Image ;   Marie Kura1 Author Orcid Image ;   Sebastian Weber2 Author Orcid Image ;   Johannes Zeichen2 Author Orcid Image ;   Wolfgang Pommer3 Author Orcid Image ;   André Baumgart4, 5 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

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  1. Caichihua Marca L, Pizarro Andrade R, Enriquez Canto Y. Determinantes funcionales del riesgo de caídas en adultos mayores. Circunferencia de pantorrilla y velocidad de marcha. Fisioterapia 2026;48(1):10 View
  2. Safarina L, Kosasih C, Pramukti M, Nursjamsi N. E-Counselling for Fall Prevention in Older Adults: A Scoping Review (Preprint). JMIR Aging 2025 View