Research graph
References from Suicide Risk Models Are Ready—Our Health Systems Are Not. Local targets link to admitted publications; unresolved targets remain external evidence.
Predicting suicide attempts and suicide deaths following outpatient visits using electronic health records.
10.1176/appi.ajp.2018.17101167 · 2018 · External reference
Natural language processing and machine learning of electronic health records for prediction of first-time suicide attempts.
10.1093/jamiaopen/ooab011 · 2021 · External reference
Prediction of fatal and non-fatal suicide attempts by the Columbia Suicide Severity Rating Scale (C-SSRS): systematic review and meta-analysis.
10.1192/bjp.2025.10316 · 2025 · External reference
Integration of face-to-face screening with real-time machine learning to predict risk of suicide among adults.
10.1001/jamanetworkopen.2022.12095 · 2022 · External reference
Prediction models for self-harm and suicide: a systematic review and critical appraisal.
10.1186/s12916-025-04367-6 · 2025 · External reference
Suicide death prediction using the Maryland Suicide Data Warehouse: a sensitivity analysis.
10.1080/13811118.2024.2363227 · 2025 · External reference
Patterns of social determinants of health and child mental health, cognition, and physical health.
10.1001/jamapediatrics.2023.4218 · 2023 · External reference
Machine learning to investigate policy-relevant social determinants of health and suicide rates in the United States.
10.1038/s44220-025-00424-4 · 2025 · External reference
Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework.
10.1093/jamia/ocad075 · 2023 · External reference
Implementing cardiovascular risk prediction in clinical practice: the future is now.
10.1161/jaha.117.006019 · 2017 · External reference
