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

AI in Older Adult Care (40) Frailty Detection, Assessment and Prediction (62) Machine Learning (2076) Computer-Aided Diagnosis (251) Artificial Intelligence (2129) Fitness Trackers and Smart Pedometers/Accelerometers (665) Wearable Devices and Sensors (1133)

Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77140, first published .
Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study

Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study

Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study

Authors of this article:

Xiaoping Zheng1 Author Orcid Image ;   Ziwei Zeng1 Author Orcid Image ;   Kimberley S van Schooten2, 3 Author Orcid Image ;   Yijian Yang1, 4 Author Orcid Image
Article Authors Cited by Tweetations Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.