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Updated: Feb 6, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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青少年心理健康的数字表型:利用机器学习进行可行性研究,从主动和被动智能手机数据中预测心理健康风险

Balasundaram Kadirvelu1, Teresa Bellido Bel2, Aglaia Freccero2

  • 1Brain & Behaviour Lab, Department of Computing and Department of Bioengineering, Imperial College London, Royal School of Mines, London, SW72AZ, United Kingdom, 44 20 7594 6373.

Journal of medical Internet research
|February 4, 2026
PubMed
概括

智能手机数字表型有效地通过整合主动和被动数据来预测青少年心理健康风险. 这种可扩展的方法有助于在非临床年轻人中早期检测,弥合了社区预防的关键差距.

关键词:
欧洲药品监督管理局 (EMA) 是一个.人工智能的人工智能是人工智能.数字健康数字健康早期干预是早期的干预.生态瞬间评估 环境瞬间评估移动健康 移动健康 移动健康 移动健康移动应用程序 移动应用程序移动健康的移动健康智能手机传感感应的感应青少年心理健康 青少年心理健康

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