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Published on in Vol 9 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/101284, first published .
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Correction: Development and Validation of Machine Learning Models for Predicting Falls Among Hospitalized Older Adults: Retrospective Cross-Sectional Study

Correction: Development and Validation of Machine Learning Models for Predicting Falls Among Hospitalized Older Adults: Retrospective Cross-Sectional Study

Authors of this article:

Xiyao Yang1 Author Orcid Image ;   Juan Ren1 Author Orcid Image ;   Dan Su2, 3 Author Orcid Image ;   Manzhen Bao1 Author Orcid Image ;   Miao Zhang1 Author Orcid Image ;   Xiaoming Chen1 Author Orcid Image ;   Yanhua Li1 Author Orcid Image ;   Zonggui Wang1 Author Orcid Image ;   Xiujing Dai1 Author Orcid Image ;   Zengzeng Wei1 Author Orcid Image ;   Shuiyu Zhang2 Author Orcid Image ;   Yuxin Zhang1 Author Orcid Image ;   Juan Li1 Author Orcid Image ;   Xiaolin Li1 Author Orcid Image ;   Junjin Xu1 Author Orcid Image ;   Nan Mo1 Author Orcid Image
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    1Second Hospital of Anhui Medical University, No.678 Furong Road, Shushan District, Hefei, China

    2School of Nursing, Anhui Medical University, Hefei, China

    3The Taikang Health and Wellness Industry Research Institute, Anhui Medical University, Hefei, China

    *these authors contributed equally

    Corresponding Author:

    Nan Mo, MSc



    In “Development and Validation of Machine Learning Models for Predicting Falls Among Hospitalized Older Adults: Retrospective Cross-Sectional Study” [1], the authors noted one error.

    In the Selection of Predictor Variables section, the following sentence was replaced:

    Univariate LR identified 27 potential predictors (P<.05) in the training set, as detailed in Table S3 of Multimedia Appendix 1.

    The sentence now reads:

    Univariate LR identified 26 potential predictors (P<.05) in the training set. The mBI did not reach statistical significance in the univariate analysis, but its P value was .054, which is very close to the threshold. Given that the mBI is an important clinical indicator associated with fall risk and to avoid omitting potentially influential factors due to a rigid threshold, we decided after expert discussion to include it as the 27th variable in the subsequent feature selection, as detailed in Table S3 of Multimedia Appendix 1.

    The correction will appear in the online version of the paper on the JMIR Publications website, together with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.

    1. Yang X, Ren J, Su D, et al. Development and validation of machine learning models for predicting falls among hospitalized older adults: retrospective cross-sectional study. JMIR Aging. Jan 5, 2026;9:e80602. [CrossRef] [Medline]

    This is a non–peer-reviewed article. submitted 16.May.2026; accepted 29.May.2026; published 13.Aug.2026.

    Copyright

    © Xiyao Yang, Juan Ren, Dan Su, Manzhen Bao, Miao Zhang, Xiaoming Chen, Yanhua Li, Zonggui Wang, Xiujing Dai, Zengzeng Wei, Shuiyu Zhang, Yuxin Zhang, Juan Li, Xiaolin Li, Junjin Xu, Nan Mo. Originally published in JMIR Aging (https://aging.jmir.org), 13.Aug.2026.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Aging, is properly cited. The complete bibliographic information, a link to the original publication on https://aging.jmir.org, as well as this copyright and license information must be included.