Monitoring Substance Use with Fitbit Biosignals: A Case Study on Training Deep Learning Models Using Ecological Momentary Assessments and Passive Sensing

Substance use disorders affect 17.3% of Americans. Digital health solutions that use machine learning to detect substance use from wearable biosignal data can eventually pave the way for real-time digital interventions. However, difficulties in addressing severe between-subject data heterogeneity ha...

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Principais autores:	Shizhe Li, Chunzhi Fan, Ali Kargarandehkordi, Yinan Sun, Christopher Slade, Aditi Jaiswal, Roberto M. Benzo, Kristina T. Phillips, Peter Washington
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2024-12-01
Serija:	AI
Teme:	wearables Fitbit substance use self-supervised learning personalized models remote monitoring
Online dostop:	https://www.mdpi.com/2673-2688/5/4/131
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