Developing a practical suicide risk prediction model for targeting high‐risk patients in the Veterans health Administration

Cited by (209)

Items 201–209 of 209

1. Enhancing personalized suicide risk prediction for VA patients by integrating discrete natural language processing models
   Monica Dimambro, Joshua Levy, Jiang Gui, Matan Goldberg, Brian R. Shiner, Maxwell Levis · 2026 · Translational Psychiatry
2. Evaluating chaplaincy utilization in a suicide-risk-stratified Veterans Affairs patient sample
   Maxwell Levis, Monica Dimambro, Joshua Levy, Brian R. Shiner · 2026 · Journal of Health Care Chaplaincy
3. Evaluating model generalizability for suicide attempt risk prediction: traditional machine vs deep learning
   Nicholas Josselyn, Sahil Sawant, Rachel E. Davis-Martin, Elke A. Rundensteiner, Ben S. Gerber, Bo Wang, A. J. Rothschild, E. Agu, Edwin D. Boudreaux, Fei-Fan Liu · 2026 · npj Mental Health Research
4. Comparing Suicide Rates Across Subpopulations of Veterans Receiving Veterans Health Administration Care, 2017–2021: The Suicide Risk Encyclopedia
   K. Saulnier, Stuart Brabbs, K. R. Dent, John F. McCarthy · 2026 · Administration and Policy in Mental Health and Mental Health Services Research
5. Characterizing aggression and suicide attempts among high-risk U.S. Veterans: Demographic, clinical, and military characteristics
   Alison Krauss, Nicholas R. Lindner, Michael S. McCloskey, Mark Andrew Ilgen, Suzannah K. Creech, Marianne S. Goodman · 2026 · Military Psychology
6. Predictive analytics to direct clinical attention to complex patients with elevated suicide risk: enhancement of the Veterans Health Administration REACH VET model
   Alina Peluso, Jorge Ramirez Osorio, William H. Kazanis, Amy Robinson, Susana B. Martins, Hope Cook, Kelley Callaway, Noah Schaefferkoetter, John F. McCarthy, Elizabeth M. Oliva et al. · 2026 · BMJ Mental Health
7. AI Models for Suicide Risk Prediction in Adult Patients Receiving Mental Health Care Using Real-World Data: Retrospective Population-Based Study
   Cleofé Peña-Gómez, Marc Fradera, Xavier Sánchez Corrales, M. Caravaca, Juan-Francisco Martínez-Cerdá, Joan Albert Escofet, David Roche, Eneko Barbería, Caridad Pontes, Jesús Giraldo et al. · 2026 · JMIR AI
8. Risk and Protective Factors of Suicidal Ideation and Attempts in Chinese Young Adults: Machine Learning Analysis of a Large Cross-Sectional Survey (Preprint)
   Shufang Sun, Zishan Jiwani, Shicun Xu, Simon Benjamin Goldberg, John Joseph Curtin, Runsen Chen · 2025 · JMIR Mental Health
9. Supervised machine learning enables identification of people with untreated substance use disorders using EHR-like data
   John L. Havlik, Michael J. Murphy, Taeho Greg Rhee, Keith N. Humphreys, Robert Alan Rosenheck · 2026 · Nature Mental Health