Identifying populations at ultra-high risk of suicide using a novel machine learning method-Reference-Cited by-同舟云学术

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Identifying populations at ultra-high risk of suicide using a novel machine learning method

Published:2023-05 Issue: Volume:123 Page:152380
ISSN:0010-440X
Container-title:Comprehensive Psychiatry
language:en
Short-container-title:Comprehensive Psychiatry

Author:

Berkelmans Guus,Schweren Lizanne,Bhulai Sandjai,van der Mei Rob,Gilissen Renske

Funder

Ministerie van Volksgezondheid, Welzijn en Sport

Publisher

Elsevier BV

Subject

Psychiatry and Mental health,Clinical Psychology

Reference17 articles.

1. Identifying socio-demographic risk factors for suicide using data on an individual level;Berkelmans;BMC Public Health,2021

2. Preventing suicide: a global imperative;World Health Organization,2014

3. Suicide risk among prisoners in French Guiana: prevalence and predictive factors;Ayhan;BMC Psychiatry,2017

4. Profile of suicide attempts and risk factors among psychiatric patients: A case-control study;Bhatt;PLOS ONE,2018

5. Risk factors of suicide attempt among people with suicidal ideation in South Korea: a cross-sectional study;Choi;BMC Public Health,2017

Cited by 4 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. Artificial Intelligence-based Suicide Prevention and Prediction: A Systematic Review (2019-2023);Information Fusion;2024-09

2. Artificial Intelligence-Based Suicide Prevention and Prediction: A Systematic Review (2019-2023);2024

3. Suicidality during the COVID-19 pandemic in the Netherlands;TSG - Tijdschrift voor gezondheidswetenschappen;2023-06-20

4. Among which socio-demographic groups is suicide most common?;TSG - Tijdschrift voor gezondheidswetenschappen;2023-06-20

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