Patient-Specific Modeling of Daily Activity Patterns for Unsupervised Detection of Psychotic and Non-Psychotic Relapses
Author:
Affiliation:
1. Technical University of Munich,TUM School of Computation, Information and Technology,Munich,Germany,80333
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10625769/10625780/10627246.pdf?arnumber=10627246
Reference4 articles.
1. Challenges and Opportunities in Global Mental Health: a Research-to-Practice Perspective
2. E-Prevention: Advanced Support System for Monitoring and Relapse Prevention in Patients with Psychotic Disorders Analyzing Long-Term Multimodal Data from Wearables and Video Captures
3. The 2nd e-Prevention Challenge: Psychotic and Non-Psychotic Relapse Detection using Wearable-Based Digital Phenotyping;Wainberg
4. SP Grand Challenge 2023 – E-Prevention: Sleep Behavior as an Indicator of Relapses in Psychotic Patients;Wainberg
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. The 2nd E-Prevention Challenge: Psychotic and Non-Psychotic Relapse Detection Using Wearable-Based Digital Phenotyping;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14
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