Gradient boosting on combined wearable biomarkers, activity, and sleep data yields 84.44% AUC for short-term weight-loss prediction in a 100-person cohort.
A Machine Learning Approach to Classifying Self-reported Health Status in a Cohort of Patients with Heart Disease Using Activity Tracker Data
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Personalized Weight Loss Management through Wearable Devices and Artificial Intelligence
Gradient boosting on combined wearable biomarkers, activity, and sleep data yields 84.44% AUC for short-term weight-loss prediction in a 100-person cohort.