ArticleNpj mental health research2022
Machine learning based suicide prediction and development of suicide vulnerability index for US counties.
Article in Npj mental health research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Predictive analytics to direct clinical attention to complex patients with elevated suicide risk: enhancement of the Veterans Health Administration REACH VET model.BMJ mental health · 2026Article
- Prediction of suicidal ideation and depression in the general population with subthreshold insomnia using machine learning models.BMC psychiatry · 2025Article
- Prevalence of bias against neurodivergence-related terms in artificial intelligence language models.Autism research : official journal of the International Society for Autism Research · 2024Article
- Do early-life circumstances predict late-life suicidal ideation? Evidence from SHARE data using machine learning.Frontiers in psychiatry · 2024Article
- Ecological Momentary Assessment and Machine Learning for Predicting Suicidal Ideation Among Sexual and Gender Minority Individuals.JAMA network open · 2023Article
- Artificial intelligence in suicide prevention: Utilizing deep learning approach for early detection.Industrial psychiatry journalArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
Suicide is a growing public health concern in the United States. A detailed understanding and prediction of suicide patterns can significantly boost targeted suicide control and prevention efforts. In this article we look at the suicide trends and geographical distribution of suicides and then develop a machine learning based US county-level suicide prediction model, using publicly available data for the 10-year period from 2010-2019. Analysis of the trends and geographical distribution of suicides revealed that nearly 25% of the total counties experienced at least a 10% increase in suicides from 2010 to 2019, with about 12% of total counties exhibiting an increase of at least 50%. An eXtreme Gradient Boosting (XGBoost) based machine learning model was used with 17 unique features for each of the 3140 counties in the US to predict suicides with an R
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Registered trials
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