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

Machine Learning (3386) Clinical Information and Decision Making (3964) Obstetrics, Gynecology, and Reproductive Medicine (439) Tools, Programs and Algorithms (618) Decision Support for Health Professionals (2402) Urology (69)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80133, first published .
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A Machine Learning–Based Model to Predict Overactive Bladder Risk Among US Women: Evidence From the National Health and Nutrition Examination Survey 2011-2018

A Machine Learning–Based Model to Predict Overactive Bladder Risk Among US Women: Evidence From the National Health and Nutrition Examination Survey 2011-2018

Authors of this article:

Guoqiang Huang1 Author Orcid Image ;   Shuangquan Lin1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Lin S, huang g. Correction: A Machine Learning-Based Model to Predict Overactive Bladder Risk Among US Women: Evidence From the National Health and Nutrition Examination Survey 2011-2018 (Preprint). JMIR Medical Informatics 2026 View