These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

182 related articles for article (PubMed ID: 32324581)

  • 1. Machine Learning Based Suicide Ideation Prediction for Military Personnel.
    Lin GM; Nagamine M; Yang SN; Tai YM; Lin C; Sato H
    IEEE J Biomed Health Inform; 2020 Jul; 24(7):1907-1916. PubMed ID: 32324581
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predicting future suicidal behaviour in young adults, with different machine learning techniques: A population-based longitudinal study.
    van Mens K; de Schepper C; Wijnen B; Koldijk SJ; Schnack H; de Looff P; Lokkerbol J; Wetherall K; Cleare S; C O'Connor R; de Beurs D
    J Affect Disord; 2020 Jun; 271():169-177. PubMed ID: 32479313
    [TBL] [Abstract][Full Text] [Related]  

  • 3. No Way Out: Entrapment as a Moderator of Suicide Ideation Among Military Personnel.
    Shelef L; Levi-Belz Y; Fruchter E; Santo Y; Dahan E
    J Clin Psychol; 2016 Oct; 72(10):1049-63. PubMed ID: 27092810
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of suicidal ideation in children and adolescents using machine learning and deep learning algorithm: A case study in South Korea where suicide is the leading cause of death.
    Shin S; Kim K
    Asian J Psychiatr; 2023 Oct; 88():103725. PubMed ID: 37595385
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Comparing machine learning to a rule-based approach for predicting suicidal behavior among adolescents: Results from a longitudinal population-based survey.
    van Vuuren CL; van Mens K; de Beurs D; Lokkerbol J; van der Wal MF; Cuijpers P; Chinapaw MJM
    J Affect Disord; 2021 Dec; 295():1415-1420. PubMed ID: 34620490
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction models for high risk of suicide in Korean adolescents using machine learning techniques.
    Jung JS; Park SJ; Kim EY; Na KS; Kim YJ; Kim KG
    PLoS One; 2019; 14(6):e0217639. PubMed ID: 31170212
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Comparison of three machine learning models to predict suicidal ideation and depression among Chinese adolescents: A cross-sectional study.
    Huang Y; Zhu C; Feng Y; Ji Y; Song J; Wang K; Yu F
    J Affect Disord; 2022 Dec; 319():221-228. PubMed ID: 36122602
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine learning prediction of suicidal ideation, planning, and attempt among Korean adults: A population-based study.
    Lee J; Pak TY
    SSM Popul Health; 2022 Sep; 19():101231. PubMed ID: 36263295
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting Suicidal Behavior Without Asking About Suicidal Ideation: Machine Learning and the Role of Borderline Personality Disorder Criteria.
    Horvath A; Dras M; Lai CCW; Boag S
    Suicide Life Threat Behav; 2021 Jun; 51(3):455-466. PubMed ID: 33185302
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Identification of Risk Factors for Suicidal Ideation and Attempt Based on Machine Learning Algorithms: A Longitudinal Survey in Korea (2007-2019).
    Choi J; Cho S; Ko I; Han S
    Int J Environ Res Public Health; 2021 Dec; 18(23):. PubMed ID: 34886497
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Suicide attempts before joining the military increase risk for suicide attempts and severity of suicidal ideation among military personnel and veterans.
    Bryan CJ; Bryan AO; Ray-Sannerud BN; Etienne N; Morrow CE
    Compr Psychiatry; 2014 Apr; 55(3):534-41. PubMed ID: 24246604
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Using Machine Learning to Predict Suicide Attempts in Military Personnel.
    Rozek DC; Andres WC; Smith NB; Leifker FR; Arne K; Jennings G; Dartnell N; Bryan CJ; Rudd MD
    Psychiatry Res; 2020 Dec; 294():113515. PubMed ID: 33113452
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Military Suicide Research Consortium common data elements: Bifactor analysis and longitudinal predictive ability of suicidal ideation and suicide attempts within a clinical sample.
    Buchman-Schmitt JM; Stanley IH; Gallyer AJ; Chu C; Gutierrez PM; Hanson JE; Joiner TE
    Psychol Assess; 2020 Jul; 32(7):609-622. PubMed ID: 32250139
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Exposure to suicide is associated with increased risk for suicidal thoughts and behaviors among National Guard military personnel.
    Bryan CJ; Cerel J; Bryan AO
    Compr Psychiatry; 2017 Aug; 77():12-19. PubMed ID: 28549312
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of recurrent suicidal behavior among suicide attempters with Cox regression and machine learning: a 10-year prospective cohort study.
    Wei YX; Liu BP; Zhang J; Wang XT; Chu J; Jia CX
    J Psychiatr Res; 2021 Dec; 144():217-224. PubMed ID: 34700209
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Predicting suicide attempts among soldiers who deny suicidal ideation in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).
    Bernecker SL; Zuromski KL; Gutierrez PM; Joiner TE; King AJ; Liu H; Nock MK; Sampson NA; Zaslavsky AM; Stein MB; Ursano RJ; Kessler RC
    Behav Res Ther; 2019 Sep; 120():103350. PubMed ID: 30598236
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review.
    Burke TA; Ammerman BA; Jacobucci R
    J Affect Disord; 2019 Feb; 245():869-884. PubMed ID: 30699872
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Agency is associated with decreased emotional distress and suicidal ideation in military personnel.
    Bryan CJ; Andreski SR; McNaughton-Cassill M; Osman A
    Arch Suicide Res; 2014; 18(3):241-50. PubMed ID: 24712868
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A proposed model of the development of suicidal ideations.
    Gvion Y; Horesh N; Levi-Belz Y; Apter A
    Compr Psychiatry; 2015 Jan; 56():93-102. PubMed ID: 25444078
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prediction of suicidal ideation in shift workers compared to non-shift workers using machine learning techniques.
    Park H; Lee K
    J Affect Disord; 2022 Jun; 307():125-132. PubMed ID: 35390350
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.