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

Formative Evaluation of Digital Health Interventions (2820) Research Instruments, Questionnaires, and Tools (665) Dementia and Cognitive Decline (590) Machine Learning (1736) Data Science (306) Diagnostic Tools in Mental Health (279) Development and Evaluation of Research Methods, Instruments and Tools (632)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54335, first published .
Early Identification of Cognitive Impairment in Community Environments Through Modeling Subtle Inconsistencies in Questionnaire Responses: Machine Learning Model Development and Validation

Early Identification of Cognitive Impairment in Community Environments Through Modeling Subtle Inconsistencies in Questionnaire Responses: Machine Learning Model Development and Validation

Early Identification of Cognitive Impairment in Community Environments Through Modeling Subtle Inconsistencies in Questionnaire Responses: Machine Learning Model Development and Validation

Authors of this article:

Hongxin Gao1 Author Orcid Image ;   Stefan Schneider2, 3, 4, 5 Author Orcid Image ;   Raymond Hernandez2, 5 Author Orcid Image ;   Jenny Harris1 Author Orcid Image ;   Danny Maupin1 Author Orcid Image ;   Doerte U Junghaenel2, 3, 4, 5 Author Orcid Image ;   Arie Kapteyn5 Author Orcid Image ;   Arthur Stone2, 3, 5 Author Orcid Image ;   Elizabeth Zelinski4 Author Orcid Image ;   Erik Meijer5 Author Orcid Image ;   Pey-Jiuan Lee2, 5 Author Orcid Image ;   Bart Orriens5 Author Orcid Image ;   Haomiao Jin1 Author Orcid Image
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Journals

  1. Ren H, Zheng Y, Li C, Jing F, Wang Q, Luo Z, Li D, Liang D, Tang W, Liu L, Cheng W. Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study. JMIR Aging 2025;8:e67437 View