Predicting Suicide Attempts and Suicide Deaths Following Outpatient Visits Using Electronic Health Records

Cited by (400)

Items 301–400 of 400

1. Why the Nails Should Boss the Hammers
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3. Anticipating Suicide Will Be Hard, But This Is Progress
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4. The Suicidal Patient
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5. A Risk Calculator to Predict Suicide Attempts Among Individuals With Early-Onset Bipolar Disorder
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6. Assessment of Suicide Risk
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7. Protocol for Designing a Model to Predict the Likelihood of Psychosis From Electronic Health Records Using Natural Language Processing and Machine Learning
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8. Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data
   Erin B. Comartin, Grant A. Victor, Athena Kheibari, Brian Kenneth Ahmedani, Bethany Hedden-Clayton, Richard Norman Jones, Ted R. Miller, Jennifer E. Johnson, Lauren M. Weinstock, Sheryl Pimlott Kubiak · 2025 · JMIR Research Protocols
9. Risk of self-harm and overdose after starting buprenorphine for opioid use disorder
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10. Managing the risk of suicide in people with treatment-resistant depression
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11. Predicting survival factor following suicide attempt in Iran: an ensemble machine learning technique
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12. A New Longitudinal Classification Method Based on Stacking Predictions for Separate Time Points
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13. Predicting imminent suicide risk in a crisis hotline chat using machine learning
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14. Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk of intentional self-harm
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15. Predicting and Preventing Suicide at Entry to Mental Health Care: A Community-Engaged, Machine Learning Model Implementation
    Honor Hsin, Santiago Papini, Yun Lu, Heather Clancy, Megan Erion, Carrie Lee, Kimberly Brochard-Des Roches, Jinghui Ju, Kristine Girard, Maria Koshy et al. · 2026 · NEJM Catalyst
16. Life events extraction from healthcare notes for veteran acute suicide risk prediction
    Destinee Morrow, Rafael Zamora‐Resendiz, Sayera Dhaubhadel, Jean C. Beckham, Nathan A. Kimbrel, Benjamin H McMahon, VA Million Veteran Program, Destinee Morrow, Rafael Zamora‐Resendiz, Sayera Dhaubhadel et al. · 2025 · Journal of the American Medical Informatics Association
17. The frequency of negative automatic thoughts may predict near-term suicide attempt in high-risk patients
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18. Suicide Risk Among Psychiatric Patients
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19. Randomized Pilot of a Clinical Decision Support Tool to Increase Suicide Screening for at-Risk Primary Care Patients With Opioid Use Disorder
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20. Considerations and Challenges When Using Clinical and Vital Record Review for Suicide Research
    Sarah A. Arias, Brandon A. Gaudiano, G. Epstein-Lubow, Sarah Zylberfuden, Lauren Weinstock · 2025 · Journal of patient safety
21. A cohort study of predictors of short-term nonfatal suicidal and self-harm events among individuals with mental health disorders treated in the emergency department
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22. Working with suicide: Evaluating gaps in training provision
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23. Risk factors for completed suicide among people who use drugs: A scoping review protocol
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24. Coulombe et al. Respond to “Baby Steps to a Learning Mental Health–Care System”
    Janie Coulombe, Erica E. M. Moodie, Susan M. Shortreed, Christel Renoux · 2020 · American Journal of Epidemiology
25. Suicide risk during the COVID-19 pandemic
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26. Implementing Predictive Models Within an Electronic Health Record System: Lessons from an External Validation of a Suicide Risk Model
    Lydia Sequeira, Douglas McNair, David Wiljer, Gillian Strudwick, Vincenzo De Luca, Kanakasaba Kailasam, Michael Thompson, Brian Chou, John Strauss · 2022 · Studies in health technology and informatics
27. Screening for Suicide Risk Is Predicting the Future, Not Diagnosing the Present
    Rebecca C. Rossom, Gregory E. Simon · 2023 · The Joint Commission Journal on Quality and Patient Safety
28. Views on sharing mental health data for research purposes: A qualitative study with people with mental illness
    E. Watson, Sue Fletcher‐Watson, Elizabeth Kirkham · 2022 · medRxiv
29. Randomized Controlled Comparative Effectiveness Trial of Risk Model-Guided Clinical Decision Support for Suicide Screening
    Colin G. Walsh, Michael A. Ripperger, Laurie Lovett Novak, Carrie Reale, Shilo H. Anders, Ashley Spann, Jhansi Kolli, Katelyn Robinson, Qingxia Chen, David Alan Isaacs et al. · 2024 · medRxiv
30. Machine Learning Models for the Prediction of Early-Onset Bipolar Using Electronic Health Records
    Bo Wang, Yi-han Sheu, Hyunjoon Lee, Robert G. Mealer, Victor Manuel Castro, Jordan W. Smoller · 2024 · medRxiv
31. LONGITUDINAL DATA PREDICTION IN EHR: COMPARISON OF GLMM AND MACHINE LEARNING METHODS
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32. Predicting Self-harm Incidents Following Inpatient Visits using Disease Comorbidity Network
    Zhongzhi Xu, Qingpeng Zhang, Paul S. F. Yip · 2020 · medRxiv
33. An approach for Risk Assessment Score of Suicide Attempt (RASSA)
    Ana Fructuoso, Inmaculada Fierro, María-Isabel Jiménez-Serranía, Alfonso Carvajal García‐Pando · 2021 · Research Square
34. PREDICTING SELF-HARM AND IDENTIFYING CAUSAL RISK FACTORS AMONG ADOLESCENTS WHO HAVE HAD CONTACT WITH U.S. CHILD PROTECTIVE SERVICES
    Geoffrey D. Kahn · 2021
35. Suicide Risk Among Psychiatric Patients
    Erkki Tapio Isometsä · 2022 · Springer eBooks
36. An approach for Risk Assessment Score of Suicide Attempt (RASSA)
    Ana Fructuoso, Inmaculada Fierro, María-Isabel Jiménez-Serranía, Alfonso Carvajal García‐Pando · 2021 · Research Square
37. The Suicidal Patient
    Sonya R. Shipley, Molly S. Clark, David R. Norris · 2020 · Springer eBooks
38. Risk factors for completed suicide among people who use drugs: A scoping review protocol
    Lisa Murphy, Suzi Lyons, Michael O’Sullivan, Ena C. Lynn · 2020 · HRB Open Research
39. The Suicidal Patient in Organ Transplantation
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40. Introduction and Overview
    IGOR I. GALYNKER · 2023 · Oxford University Press eBooks
41. Suicide Preventive Interventions and Knowledge
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42. Losing a Patient or Colleague to Suicide
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43. Inference on summaries of a model-agnostic longitudinal variable importance trajectory with application to suicide prevention
    Brian D. Williamson, Erica E. M. Moodie, Gregory E. Simon, Rebecca C. Rossom, Susan M. Shortreed · 2026 · The Annals of Applied Statistics
44. Correcting Overestimations in Self-Harm Visit Data: Response From Bommersbach and Colleagues
    Tanner J. Bommersbach, Mark Olfson, Taeho Greg Rhee · 2025 · American Journal of Psychiatry
45. Artificial Intelligence Outperforms Standard Screening Tools for Predicting Suicide Risk
    Dan Hurley · 2025 · Neurology Today
46. Accuracy of Self-Report Questionnaires and Records-Based Risk Scores to Identify Adolescents’ Risk for Self-Harm
    Gregory E. Simon, Christine C. Stewart, Julie Angerhofer Richards, Rebecca A. Ziebell, Gwen T. Lapham, Andrea J. Hoopes · 2025 · Psychiatric Services
47. Predicting and Preventing Suicide at Entry to Mental Health Care: A Community-Engaged, Machine Learning Model Implementation
    Honor Hsin, Santiago Papini, Yun Lu, Heather Clancy, Megan Erion, Carrie Lee, Kimberly Brochard-Des Roches, Jinghui Ju, Kristine Girard, Maria T. Koshy et al. · 2025 · medRxiv
48. Advancing Suicide Prediction with Adaptive Sentiment Module and Transformer Architecture
    Huanbo Yang · 2024 · International Conference on Big Data, Artificial Intelligence and Risk Management (ICBAR)
49. Developing a suicide risk prediction model for hospitalized adolescents with depression in China
    Juan Zhao, Ying Li, Yangjie Chen, Ahmad Naqib Shuid · 2025 · Frontiers in Psychiatry
50. Evaluating Clinical Implementation of Risk Prediction Based Interventions Using Difference‐In‐Differences
    Maricela Cruz, Susan M. Shortreed, Gregory E. Simon, Rebecca Yates Coley · 2025 · Health Services Research
51. Suicide risk prediction for users with depression in question answering communities: A design based on deep learning
    Haoyue Fan, Qiuju Yin, Junwei Kuang, Zhijun Yan · 2025 · Information & Management
52. AI-based algorithms trained with real-world data for suicide risk prevention in adult mental health patients: The IDICIUS Project. (Preprint)
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53. Artificial Intelligence in Public Health
    Ian M. Bennett, Bela T. Matyas · 2025 · Primary Care Clinics in Office Practice
54. Hormonal contraception and the risk of suicidal behaviour: a Swedish nationwide register-based study
    Jūratė Aleknavičiūtė, Donghao Lu, Agnes Ohlsson Gotby, Emma Maria Frans, Ralf Kuja‐Halkola, Hedvig Engberg, Henning W. Tiemeier, Paul Lichtenstein, Fang Fang, Steven A. Kushner et al. · 2025 · BMJ Open
55. Detecting Undiagnosed Mental Health Conditions Using Positive and Unlabeled Learning: Identifying Uncoded Self-Harm in Veterans’ Electronic Health Records (Preprint)
    Praveen Kumar, Alexandria D. Viszolay, Rajesh Upadhayaya, Fariha Moomtaheen, Donald R. Greer, Cristian Bologa, Kristan Alexander Schneider, Sharon E. Davis, Michael Edwin Matheny, David N. van der Goes et al. · 2025
56. Additional file 1 of Empirical evaluation of internal validation methods for prediction in large-scale clinical data with rare-event outcomes: a case study in suicide risk prediction
    Rebecca Yates Coley, Qinqing Liao, Noah Simon, Susan M. Shortreed · 2023 · Figshare
57. Additional file 1 of Clinical implementation of suicide risk prediction models in healthcare: a qualitative study
    Bobbi Jo H. Yarborough, Scott P. Stumbo, Schneider, Jennifer, Richards, Julie E., Stephanie Ann Hooker, Rebecca C. Rossom · 2023 · Figshare
58. Additional file 1 of Patient expectations of and experiences with a suicide risk identification algorithm in clinical practice
    Bobbi Jo H. Yarborough, Scott P. Stumbo, Schneider, Jennifer L., Richards, Julie E., Stephanie Ann Hooker, Rebecca C. Rossom · 2022 · Figshare
59. Additional file 1 of Electronic health records identify timely trends in childhood mental health conditions
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60. Additional file 3 of Adolescent, parent, and provider attitudes toward a machine learning based clinical decision support system for selecting treatment for youth depression
    Meredith Gunlicks‐Stoessel, Yangchenchen Liu, Catherine Parkhill, Nicole Morrell, Mimi Choy-Brown, Christopher J. Mehus, Joel Hetler, Gerald J. August · 2024 · Figshare
61. Additional file 1 of Views on sharing mental health data for research purposes: qualitative analysis of interviews with people with mental illness
    Watson, Emily, Sue Fletcher‐Watson, Elizabeth Kirkham · 2023 · Figshare
62. Additional file 1 of Suicide typologies among Medicaid beneficiaries, North Carolina 2014–2017
    Josie J. Caves Sivaraman, Shabbar I. Ranapurwala, Scott Proescholdbell, Rebecca B. Naumann, Sandra B. Greene, Marshall, Stephen W. · 2022 · Figshare
63. Additional file 2 of Adolescent, parent, and provider attitudes toward a machine learning based clinical decision support system for selecting treatment for youth depression
    Meredith Gunlicks‐Stoessel, Yangchenchen Liu, Catherine Parkhill, Nicole Morrell, Mimi Choy-Brown, Christopher J. Mehus, Joel Hetler, Gerald J. August · 2024 · Figshare
64. Additional file 2 of Electronic health records identify timely trends in childhood mental health conditions
    Josephine Elia, KATHLEEN A. PAJER, Raghuram Prasad, Pumariega, Andres, Maltenfort, Mitchell, Utidjian, Levon, Shenkman, Elizabeth, Kelly J. Kelleher, Rao, Suchitra, Peter A. Margolis et al. · 2023 · Figshare
65. Additional file 1 of Adolescent, parent, and provider attitudes toward a machine learning based clinical decision support system for selecting treatment for youth depression
    Meredith Gunlicks‐Stoessel, Yangchenchen Liu, Catherine Parkhill, Nicole Morrell, Mimi Choy-Brown, Christopher J. Mehus, Joel Hetler, Gerald J. August · 2024 · Figshare
66. Predicting and differentiating opioid and non-opioid drug poisonings using health records data
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67. An Explainable Triple‐Layered Ensemble Model for Early Prediction of Suicide Risk Using Machine Learning
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68. Suicidal ideation trajectories among adults following psychiatric hospitalization
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69. The impact of violence at home to psychoemotional distress, well-being and suicidal risk: a massive mental health screening using smartphones
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70. When is Suicide Unexpected? A Normative-Explanatory Account of Suicidal Action
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71. Parental violent offending and offspring suicidal behavior: a nationwide register-based study
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72. Validation of a Risk‐Prediction Model in the Presence of Outcome Misclassification
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73. Detecting Uncoded Self-Harm in Veterans’ Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Cohort Study
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74. Evaluating model generalizability for suicide attempt risk prediction: traditional machine vs deep learning
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75. Multimodal AI in Suicide Risk Prediction: Behavioral, Physiological, and Digital Biomarkers
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76. Early detection of high-risk users in a digital peer-to-peer mental health support platform
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77. A hierarchical machine learning model for predicting self-harm and suicidal behaviour in hospitalised patients with schizophrenia using clinical history and nursing observations
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78. Design and Validation of an AI-Assisted Sequential Screening Framework for Psychological Distress in Glaucoma
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79. AI Models for Suicide Risk Prediction in Adult Patients Receiving Mental Health Care Using Real-World Data: Retrospective Population-Based Study
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80. Predicting and differentiating accidental and self-harm drug poisonings using health records data
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82. Association of digital patient-reported outcome measures (PROMs) with clinical outcomes in out-patient mental healthcare: multicentre, cross-sectional study
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83. Situated vulnerabilities and resiliencies associated with lifetime and past 6-month suicide attempt among transgender and gender diverse primary care patients
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86. The Suicidal Patient
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88. Using Large Language Models to Identify Suicide Risk Factors in Pediatric Emergency Department Chart Notes
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89. A Clinical Prediction Model for Self-Harm After Adolescent Traumatic Brain Injury
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91. Comunicación estratégica de organizaciones de prevención del suicidio en redes sociales: Planificación, contenidos e interacción
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93. Predicting suicide attempts in people with autism and co-morbid mood or psychotic disorders
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94. Identification of prospective short-term risk factors for suicidal ideation and non-fatal suicide attempts in a large cohort of adults with recent suicidal ideation
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96. Considerations for implementing a machine learning model for suicide risk in the health systems that serve American Indian communities
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97. Multimodal machine-learning discrimination of recent preadmission suicidal behavior in adolescents hospitalized with depressive episodes
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98. Predicting Self-Harm Events After Emergency Department Visits Associated With Mental or Substance Use Disorder Diagnoses
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99. Generative Large Language Models for Psychiatric Concept Detection in Spanish-Language Electronic Health Records: Development and Evaluation Study
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100. Polygenic dissection of suicidal thoughts and behaviours in high-risk mood-disorder cohorts
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