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Updated: May 28, 2025

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通过现实世界的数据和健康的社会决定因素来识别青少年抑郁和焦虑:机器学习模型开发和验证

Mamoun T Mardini1, Georges E Khalil1, Chen Bai1

  • 1Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 7th Floor, Suite 7000, 1889 Museum Rd, Gainesville, FL, 32611, United States, 1 7049045847.

JMIR mental health
|February 12, 2025
PubMed
概括

机器学习模型有效地使用现实数据识别青少年抑郁和焦虑. 这种方法有助于早期发现和干预,改善年轻人的心理健康结果.

关键词:
沙普利添加剂扩展法 沙普利添加剂扩展法在XGBoost中使用.青少年 青少年 青少年焦虑是一种焦虑.临床数据 临床数据交叉验证技术的交叉验证技术抑郁 抑郁症 抑郁症 抑郁症 是一种健康结果的健康结果.机器学习是机器学习.精神障碍 精神障碍是一种精神障碍.心理健康 心理健康精神疾病 精神疾病现实世界的数据数据.健康的社会决定因素青少年 青少年 青少年年轻人年轻人年轻人年轻人年轻人年轻人

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