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Citing this Article

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Published on 22.06.18 in Vol 5, No 2 (2018): Apr-Jun

This paper is in the following e-collection/theme issue:

Works citing "Using Neural Networks with Routine Health Records to Identify Suicide Risk: Feasibility Study"

Marcos DelPozo-Banos, Ann John, Nicolai Petkov, Damon Mark Berridge, Kate Southern, Keith LLoyd, Caroline Jones, Sarah Spencer, Carlos Manuel Travieso

JMIR Ment Health 2018 (Jun 22); 5(2):e10144 

According to Crossref, the following articles are citing this article (DOI 10.2196/10144):

(note that this is only a small subset of citations)

  1. Jayasinghe L, Bittar A, Dutta R, Stewart R. Clinician-recalled quoted speech in electronic health records and risk of suicide attempt: a case–crossover study. BMJ Open 2020;10(4):e036186
    CrossRef
  2. Kumar P, Nestsiarovich A, Nelson SJ, Kerner B, Perkins DJ, Lambert CG. Imputation and characterization of uncoded self-harm in major mental illness using machine learning. Journal of the American Medical Informatics Association 2020;27(1):136
    CrossRef
  3. Xu Z, Zhang Q, Yip PSF. Predicting post-discharge self-harm incidents using disease comorbidity networks: A retrospective machine learning study. Journal of Affective Disorders 2020;277:402
    CrossRef
  4. Bernert RA, Hilberg AM, Melia R, Kim JP, Shah NH, Abnousi F. Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations. International Journal of Environmental Research and Public Health 2020;17(16):5929
    CrossRef
  5. Martínez-Alés G, Keyes KM. Fatal and Non-fatal Self-Injury in the USA: Critical Review of Current Trends and Innovations in Prevention. Current Psychiatry Reports 2019;21(10)
    CrossRef
  6. John A, DelPozo-Banos M, Gunnell D, Dennis M, Scourfield J, Ford DV, Kapur N, Lloyd K. Contacts with primary and secondary healthcare prior to suicide: case–control whole-population-based study using person-level linked routine data in Wales, UK, 2000–2017. The British Journal of Psychiatry 2020;217(6):717
    CrossRef
  7. Belsher BE, Smolenski DJ, Pruitt LD, Bush NE, Beech EH, Workman DE, Morgan RL, Evatt DP, Tucker J, Skopp NA. Prediction Models for Suicide Attempts and Deaths. JAMA Psychiatry 2019;76(6):642
    CrossRef
  8. Posada-Quintero HF, Molano-Vergara PN, Parra-Hernández RM, Posada-Quintero JI. Analysis of Risk Factors and Symptoms of Burnout Syndrome in Colombian School Teachers under Statutes 2277 and 1278 Using Machine Learning Interpretation. Social Sciences 2020;9(3):30
    CrossRef
  9. McHugh CM, Large MM. Can machine-learning methods really help predict suicide?. Current Opinion in Psychiatry 2020;33(4):369
    CrossRef
  10. D’Hotman D, Loh E, Savulescu J. AI-enabled suicide prediction tools: ethical considerations for medical leaders. BMJ Leader 2021;5(2):102
    CrossRef
  11. Naghavi A, Teismann T, Asgari Z, Mohebbian MR, Mansourian M, Mañanas M. Accurate Diagnosis of Suicide Ideation/Behavior Using Robust Ensemble Machine Learning: A University Student Population in the Middle East and North Africa (MENA) Region. Diagnostics 2020;10(11):956
    CrossRef
  12. . Using Machine Learning in Burnout Prediction: A Survey. Child and Adolescent Social Work Journal 2021;38(2):175
    CrossRef
  13. Corke M, Mullin K, Angel-Scott H, Xia S, Large M. Meta-analysis of the strength of exploratory suicide prediction models; from clinicians to computers. BJPsych Open 2021;7(1)
    CrossRef
  14. D’Hotman D, Loh E. AI enabled suicide prediction tools: a qualitative narrative review. BMJ Health & Care Informatics 2020;27(3):e100175
    CrossRef
  15. Castillo-Sánchez G, Marques G, Dorronzoro E, Rivera-Romero O, Franco-Martín M, De la Torre-Díez I. Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review. Journal of Medical Systems 2020;44(12)
    CrossRef
  16. Gupta M, Ramar D, Vijayan R, Gupta N. Artificial Intelligence Tools for Suicide Prevention in Adolescents and Young Adults. Adolescent Psychiatry 2022;12(1):1
    CrossRef
  17. Lara-González LR, Delgado-Luna MA, De León-Galván BE, Venegas-Guerrero JC. Comparison of Machine Learning algorithms for the Burnout projection. ECORFAN Journal-Democratic Republic of Congo 2021;:1
    CrossRef
  18. Gupta M, Gupta N, Robinson M. A panorama of the medicolegal aspects of suicide assessments: integrating multiple vantage points in improving quality, safety, and risk management. CNS Spectrums 2023;28(3):282
    CrossRef
  19. Kirtley OJ, van Mens K, Hoogendoorn M, Kapur N, de Beurs D. Translating promise into practice: a review of machine learning in suicide research and prevention. The Lancet Psychiatry 2022;9(3):243
    CrossRef
  20. Chen S, Huang H, Liu S, Chen S. Prediction of Repeated Self-Harm in Six Months: Comparison of Traditional Psychometrics With Random Forest Algorithm. OMEGA - Journal of Death and Dying 2024;88(4):1403
    CrossRef
  21. Balbuena LD, Baetz M, Sexton JA, Harder D, Feng CX, Boctor K, LaPointe C, Letwiniuk E, Shamloo A, Ishwaran H, John A, Brantsæter AL. Identifying long-term and imminent suicide predictors in a general population and a clinical sample with machine learning. BMC Psychiatry 2022;22(1)
    CrossRef
  22. Rees S, Fry R, Davies J, John A, Condon L, Page K. Can routine data be used to estimate the mental health service use of children and young people living on Gypsy and Traveller sites in Wales? A feasibility study. PLOS ONE 2023;18(2):e0281504
    CrossRef
  23. Baniadamdizaj S, Baniadamdizaj S. Prediction of Iranian EFL teachers' burnout level using machine learning algorithms and maslach burnout inventory. Iran Journal of Computer Science 2023;6(1):1
    CrossRef
  24. Zhang J, Liang S, Liu X, Li D, Zhou F, Xiao L, Liu J, Sha S. Factors associated with suicidal attempts in female patients with mood disorder. Frontiers in Public Health 2023;11
    CrossRef
  25. Abdulazeem H, Whitelaw S, Schauberger G, Klug SJ, Vathy-Fogarassy . A systematic review of clinical health conditions predicted by machine learning diagnostic and prognostic models trained or validated using real-world primary health care data. PLOS ONE 2023;18(9):e0274276
    CrossRef
  26. Somé NH, Noormohammadpour P, Lange S. The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review. Frontiers in Psychiatry 2024;15
    CrossRef
  27. Pirrolas OAC, Correia PMAR. Human Resources’ Burnout. Encyclopedia 2024;4(1):488
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/10144):

  1. Martinez-Ales G, Hernandez-Calle D, Khauli N, Keyes KM. Behavioral Neurobiology of Suicide and Self Harm. 2020. Chapter 158:1
    CrossRef
  2. Larsen ME, Vo LC, Pratap A, Peters D. Tasman’s Psychiatry. 2023. Chapter 148-1:1
    CrossRef