Literature DB >> 31642876

Machine Learning for Suicide Research-Can It Improve Risk Factor Identification?

Seena Fazel1, Lauren O'Reilly2.   

Abstract

Entities:  

Year:  2020        PMID： 31642876      PMCID： PMC7116325          DOI： 10.1001/jamapsychiatry.2019.2896

Source DB:  PubMed          Journal:  JAMA Psychiatry        ISSN： 2168-622X            Impact factor:   21.596


× No keyword cloud information.
  10 in total

1.  Predicting suicides after psychiatric hospitalization in US Army soldiers: the Army Study To Assess Risk and rEsilience in Servicemembers (Army STARRS).

Authors:  Ronald C Kessler; Christopher H Warner; Christopher Ivany; Maria V Petukhova; Sherri Rose; Evelyn J Bromet; Millard Brown; Tianxi Cai; Lisa J Colpe; Kenneth L Cox; Carol S Fullerton; Stephen E Gilman; Michael J Gruber; Steven G Heeringa; Lisa Lewandowski-Romps; Junlong Li; Amy M Millikan-Bell; James A Naifeh; Matthew K Nock; Anthony J Rosellini; Nancy A Sampson; Michael Schoenbaum; Murray B Stein; Simon Wessely; Alan M Zaslavsky; Robert J Ursano
Journal:  JAMA Psychiatry       Date:  2015-01       Impact factor: 21.596

2.  A calibration hierarchy for risk models was defined: from utopia to empirical data.

Authors:  Ben Van Calster; Daan Nieboer; Yvonne Vergouwe; Bavo De Cock; Michael J Pencina; Ewout W Steyerberg
Journal:  J Clin Epidemiol       Date:  2016-01-06       Impact factor: 6.437

3.  Low intelligence test scores in 18 year old men and risk of suicide: cohort study.

Authors:  D Gunnell; P K E Magnusson; F Rasmussen
Journal:  BMJ       Date:  2004-12-22

4.  A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models.

Authors:  Evangelia Christodoulou; Jie Ma; Gary S Collins; Ewout W Steyerberg; Jan Y Verbakel; Ben Van Calster
Journal:  J Clin Epidemiol       Date:  2019-02-11       Impact factor: 6.437

5.  Reporting of artificial intelligence prediction models.

Authors:  Gary S Collins; Karel G M Moons
Journal:  Lancet       Date:  2019-04-20       Impact factor: 79.321

6.  Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

Authors:  Jaimie L Gradus; Anthony J Rosellini; Erzsébet Horváth-Puhó; Amy E Street; Isaac Galatzer-Levy; Tammy Jiang; Timothy L Lash; Henrik T Sørensen
Journal:  JAMA Psychiatry       Date:  2020-01-01       Impact factor: 21.596

Review 7.  Suicide and suicidal behaviour.

Authors:  Gustavo Turecki; David A Brent
Journal:  Lancet       Date:  2015-09-15       Impact factor: 79.321

8.  Association of an Early Intervention Service for Psychosis With Suicide Rate Among Patients With First-Episode Schizophrenia-Spectrum Disorders.

Authors:  Sherry Kit Wa Chan; Stephanie Wing Yan Chan; Herbert H Pang; Kang K Yan; Christy Lai Ming Hui; Wing Chung Chang; Edwin Ho Ming Lee; Eric Yu Hai Chen
Journal:  JAMA Psychiatry       Date:  2018-05-01       Impact factor: 21.596

Review 9.  How accurate are suicide risk prediction models? Asking the right questions for clinical practice.

Authors:  Daniel Whiting; Seena Fazel
Journal:  Evid Based Ment Health       Date:  2019-06-27

10.  The prediction of suicide in severe mental illness: development and validation of a clinical prediction rule (OxMIS).

Authors:  Seena Fazel; Achim Wolf; Henrik Larsson; Susan Mallett; Thomas R Fanshawe
Journal:  Transl Psychiatry       Date:  2019-02-25       Impact factor: 6.222
  10 in total
  9 in total

1.  Multimodal Neuroimaging of Suicidal Thoughts and Behaviors in a U.S. Population-Based Sample of School-Age Children.

Authors:  Pablo Vidal-Ribas; Delfina Janiri; Gaelle E Doucet; Narun Pornpattananangkul; Dylan M Nielson; Sophia Frangou; Argyris Stringaris
Journal:  Am J Psychiatry       Date:  2021-01-21       Impact factor: 18.112

2.  Suicide prediction among men and women with depression: A population-based study.

Authors:  Tammy Jiang; Dávid Nagy; Anthony J Rosellini; Erzsébet Horváth-Puhó; Katherine M Keyes; Timothy L Lash; Sandro Galea; Henrik T Sørensen; Jaimie L Gradus
Journal:  J Psychiatr Res       Date:  2021-08-11       Impact factor: 5.250

3.  The Effectiveness of Predicting Suicidal Ideation through Depressive Symptoms and Social Isolation Using Machine Learning Techniques.

Authors:  Sunhae Kim; Kounseok Lee
Journal:  J Pers Med       Date:  2022-03-22

4.  Enhanced Performance by Interpretable Low-Frequency Electroencephalogram Oscillations in the Machine Learning-Based Diagnosis of Post-traumatic Stress Disorder.

Authors:  Miseon Shim; Chang-Hwan Im; Seung-Hwan Lee; Han-Jeong Hwang
Journal:  Front Neuroinform       Date:  2022-04-26       Impact factor: 3.739

5.  Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries.

Authors:  Jaimie L Gradus; Anthony J Rosellini; Erzsébet Horváth-Puhó; Tammy Jiang; Amy E Street; Isaac Galatzer-Levy; Timothy L Lash; Henrik T Sørensen
Journal:  Am J Epidemiol       Date:  2021-12-01       Impact factor: 4.897

6.  Screening for Depression in Mobile Devices Using Patient Health Questionnaire-9 (PHQ-9) Data: A Diagnostic Meta-Analysis via Machine Learning Methods.

Authors:  Sunhae Kim; Kounseok Lee
Journal:  Neuropsychiatr Dis Treat       Date:  2021-11-20       Impact factor: 2.570

7.  Predicting suicide attempt or suicide death following a visit to psychiatric specialty care: A machine learning study using Swedish national registry data.

Authors:  Qi Chen; Yanli Zhang-James; Eric J Barnett; Paul Lichtenstein; Jussi Jokinen; Brian M D'Onofrio; Stephen V Faraone; Henrik Larsson; Seena Fazel
Journal:  PLoS Med       Date:  2020-11-06       Impact factor: 11.069

8.  Which PHQ-9 Items Can Effectively Screen for Suicide? Machine Learning Approaches.

Authors:  Sunhae Kim; Hye-Kyung Lee; Kounseok Lee
Journal:  Int J Environ Res Public Health       Date:  2021-03-24       Impact factor: 3.390

9.  Heterogeneity in gender dysphoria in a Brazilian sample awaiting gender-affirming surgery: a data-driven analysis.

Authors:  Dhiordan Cardoso Silva; Francisco Diego Rabelo-da-Ponte; Leonardo Romeira Salati; Maria Inês Rodrigues Lobato
Journal:  BMC Psychiatry       Date:  2022-02-02       Impact factor: 3.630
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.