ArticleAmerican journal of epidemiology2021
Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries.
Article in American journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.
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Who cites it
19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 30 citations in OpenAlex.
- Prediction models for self-harm and suicide: a systematic review and critical appraisal.BMC medicine · 2025Pooled it
- Machine learning algorithms and their predictive accuracy for suicide and self-harm: Systematic review and meta-analysis.PLoS medicine · 2025Pooled it
- Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies.BMC medical informatics and decision making · 2024Pooled it
- Leveraging electronic health record data for precision medicine insights: the precision medicine registry at NYU Langone Health.npj health systems · 2026Article
- Developing a Prediction Model for Suicidality Among COVID-19 Patients in Korea Using Timely Data From the National Center for Disaster and Trauma.Journal of Korean medical science · 2025Article
- Identifying most important predictors for suicidal thoughts and behaviours among healthcare workers active during the Spain COVID-19 pandemic: a machine-learning approach.Epidemiology and psychiatric sciences · 2025Article
- Weak and unstable prediction of personality from the structural connectome.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Prediction of suicide attempts among persons with depression: a population-based case cohort study.American journal of epidemiology · 2024Article
- Optimising the use of electronic medical records for large scale research in psychiatry.Translational psychiatry · 2024Review
- Evaluating the clinical utility of an easily applicable prediction model of suicide attempts, newly developed and validated with a general community sample of adults.BMC psychiatry · 2024Article
- Report on the Joint Workshop on the Relations between Health Inequalities, Ageing and Multimorbidity, Iceland, May 3-4, 2023.Clinical epidemiology · 2024Article
- Article
- County-level estimates of suicide mortality in the USA: a modelling study.The Lancet. Public health · 2023Article
- NSSI questionnaires revisited: A data mining approach to shorten the NSSI questionnaires.PloS one · 2023Article
- Emerging role of artificial intelligence in global health care.Health policy and technology · 2022Article
- Predicting the Risk of Future Multiple Suicide Attempt among First-Time Suicide Attempters: Implications for Suicide Prevention Policy.Healthcare (Basel, Switzerland) · 2022Article
- Gradus et al. Respond to "Machine Learning and Suicide Prevention: New Directions".American journal of epidemiology · 2021Article
- Stress Disorders and the Risk of Nonfatal Suicide Attempts in the Danish Population.Journal of traumatic stress · 2021Article
- Invited Commentary: New Directions in Machine Learning Analyses of Administrative Data to Prevent Suicide-Related Behaviors.American journal of epidemiology · 2021Article
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8 authors at 4 institutions in 2 countries.
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Abstract
Suicide attempts are a leading cause of injury globally. Accurate prediction of suicide attempts might offer opportunities for prevention. This case-cohort study used machine learning to examine sex-specific risk profiles for suicide attempts in Danish nationwide registry data. Cases were all persons who made a nonfatal suicide attempt between 1995 and 2015 (n = 22,974); the subcohort was a 5% random sample of the population at risk on January 1, 1995 (n = 265,183). We developed sex-stratified classification trees and random forests using 1,458 predictors, including demographic factors, family histories, psychiatric and physical health diagnoses, surgery, and prescribed medications. We found that substance use disorders/treatment, prescribed psychiatric medications, previous poisoning diagnoses, and stress disorders were important factors for predicting suicide attempts among men and women. Individuals in the top 5% of predicted risk accounted for 44.7% of all suicide attempts among men and 43.2% of all attempts among women. Our findings illuminate novel risk factors and interactions that are most predictive of nonfatal suicide attempts, while consistency between our findings and previous work in this area adds to the call to move machine learning suicide research toward the examination of high-risk subpopulations.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.