Machine Learning for Suicide Research–Can It Improve Risk Factor Identification?
Author:
Affiliation:
1. Department of Psychiatry, University of Oxford, Oxford, Oxfordshire, England
2. Indiana University, Bloomington
Publisher
American Medical Association (AMA)
Subject
Psychiatry and Mental health
Link
https://jamanetwork.com/journals/jamapsychiatry/articlepdf/2753011/jamapsychiatry_fazel_2019_ed_190027.pdf
Reference11 articles.
1. Prediction of sex-specific suicide risk using machine learning and single-payer health care registry data from Denmark [published online October 23, 2019].;Gradus;JAMA Psychiatry
2. Suicide and suicidal behaviour.;Turecki;Lancet,2016
3. Association of an early intervention service for psychosis with suicide rate among patients with first-episode schizophrenia-spectrum disorders.;Chan;JAMA Psychiatry,2018
4. A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models.;Christodoulou;J Clin Epidemiol,2019
5. How accurate are suicide risk prediction models? asking the right questions for clinical practice.;Whiting;Evid Based Ment Health,2019
Cited by 28 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. How do explicit, implicit, and sociodemographic measures relate to concurrent suicidal ideation? A comparative machine learning approach;Suicide and Life-Threatening Behavior;2023-11-13
2. Machine learning techniques in diagnostics and prediction of the clinical features of schizophrenia: a narrative review;Consortium Psychiatricum;2023-09-29
3. Suicide risk classification with machine learning techniques in a large Brazilian community sample;Psychiatry Research;2023-07
4. Interpersonal Well-Being and Suicidal Outcomes in a Nationally Representative Study of Adolescents: A Translational Study;Research on Child and Adolescent Psychopathology;2023-05-24
5. The use of advanced technology and statistical methods to predict and prevent suicide;Nature Reviews Psychology;2023-04-06
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3