AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts

AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts

Abstract Purpose Effective patient monitoring is crucial for timely healthcare interventions and improved outcomes, especially in managing conditions influenced by stress and depression, which can manifest through physiological changes. Traditional monitoring systems often struggle with the complexi...

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Bibliographic Details
Main Authors: Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Hong-Ning Dai, Feng Zhao, Jianming Yong
Format: Article
Language:English
Published: SpringerOpen 2025-06-01
Series:Brain Informatics
Subjects:
Behavior patterns
Decision making
Patient monitoring
Reinforcement learning
Vital signs
Online Access:https://doi.org/10.1186/s40708-025-00262-1
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