钥匙(锁)
抑郁症状
人口
老年学
心理学
医学
计算机科学
精神科
环境卫生
计算机安全
认知
作者
Thu Tran,Yi Zhen Tan,Sapphire H. Lin,Fang Zhao,Yee Sien Ng,Dong Ma,JeongGil Ko,Rajesh Krishna Balan
标识
DOI:10.1016/j.archger.2024.105647
摘要
This paper aims to investigate the key factors, including demographics, socioeconomics, physical well-being, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using machine learning techniques. By identifying the most important predictors of depressive symptoms through the analysis, the findings can have important implications for early depression detection and intervention.
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