摘要
全球每年有80万人死于自杀,自杀未遂数量大约是其20倍。自杀不仅是严重的公共卫生事件,而且对自杀者周围的人产生重大而深远的影响。更准确、便捷、及时地预测自杀行为一直是研究者的目标。论文对近五年应用于自杀意念与行为的机器学习研究进行回顾,分析机器学习用于自杀研究的有效性、可行性,对机器学习应用于自杀领域的研究提出建议,为未来的研究提供方向。
A total of 800,000 people die of suicide every year over the world,and the number of attempted suicides is about 20 times number of suicide.Suicide not only is a serious public health event,but also significantly and far-reachingly impact on people around suicides.More accurate,convenient,and timely prediction of suicidal behavior has always been the goal of researchers.This study summarized the researches on machine learning applied to suicidal ideation and behavior in the past 5 years,analyzed the effectiveness and feasibility of machine learning for suicide research,made recommendations,and provided a direction for future research.
作者
况利
徐小明
曾琪
KUANG Li;XU Xiaoming;ZENG Qi(Department of Psychiatry,The First Affiliated Hospital of Chongqing Medical University,Chongqing 400016,China;Mental Health Center,University-Town Hospital of Chongqing Medical University,Chongqing 401331,China)
出处
《山东大学学报（医学版）》
CAS
北大核心
2022年第4期10-16,共7页
Journal of Shandong University:Health Sciences
基金
国家自然科学基金(81671360,81971286)
重庆市自然科学基金(cstc2018jcyjAX0164)
重庆市科卫联合医学科研项目(2018QNXM014)
重庆市社会事业与民生保障科技创新专项重点研发项目(cstc2017shms-zdyfX0038)
关键词
机器学习
自杀
自杀未遂
自杀意念
大数据
Machine learning
Suicide
Suicide attempt
Suicidal ideation
Big data
