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

Formative Evaluation of Digital Health Interventions (2422) Fitness Trackers and Smart Pedometers/Accelerometers (561) Artificial Intelligence (1377) Dementia and Cognitive Decline (484) Wearable Devices and Sensors (890) Machine Learning (1471)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55575, first published .
Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

Authors of this article:

Qidi Xu1 Author Orcid Image ;   Yejin Kim1 Author Orcid Image ;   Karen Chung2 Author Orcid Image ;   Paul Schulz2 Author Orcid Image ;   Assaf Gottlieb1 Author Orcid Image
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