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Updated: May 30, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

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使用风险和保护因素框架预测青少年中的欺凌受害者:一个大规模的机器学习方法

Ethan Low1, Joshua Monsen2, Lindsay Schow2

  • 1Computer Science, Brigham Young University, Provo, 84602, Utah, USA.

BMC public health
|January 25, 2025
PubMed
概括

青少年欺凌与年轻,社会排斥和家庭问题有关. 早期饮酒是网络欺凌的关键风险因素,突出了针对性预防策略的需要.

关键词:
青少年 青少年 青少年欺凌 成为受害者 成为受害者机器学习 机器学习风险和预防风险和预防

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