ArticleInternational journal of environmental research and public health2021
Development of a Suicide Prediction Model for the Elderly Using Health Screening Data.
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 5 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 5 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- 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
- The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review.Frontiers in psychiatry · 2024Pooled it
- Application of machine learning in measurement of ageing and geriatric diseases: a systematic review.BMC geriatrics · 2023Pooled it
- Evidence for the biopsychosocial model of suicide: a review of whole person modeling studies using machine learning.Frontiers in psychiatry · 2023Pooled it
- Machine learning in mental health promotion for older adults: a scoping review.BMC geriatrics · 2026Article
- Predictive models for active suicidal ideation in cognitive decline: identifying risk factors.BMC psychiatry · 2026Article
- Automatically extracting social determinants of health for suicide: a narrative literature review.Npj mental health research · 2024Review
- Development of an AI-Based Suicide Ideation Prediction Model for People with Disabilities.Life (Basel, Switzerland) · 2024Article
- Predicting Suicidal Ideation, Planning, and Attempts among the Adolescent Population of the United States.Healthcare (Basel, Switzerland) · 2024Article
- Is It Correct to Consider Caustic Ingestion as a Nonviolent Method of Suicide? A Retrospective Analysis and Psychological Considerations.International journal of environmental research and public health · 2023Article
- Machine learning prediction of suicidal ideation, planning, and attempt among Korean adults: A population-based study.SSM - population health · 2022Article
- Machine Learning Algorithm-Based Prediction Model for the Augmented Use of Clozapine with Electroconvulsive Therapy in Patients with Schizophrenia.Journal of personalized medicine · 2022Article
- Artificial intelligence and suicide prevention: a systematic review.European psychiatry : the journal of the Association of European Psychiatrists · 2022Review
- The Development of a Suicidal Ideation Predictive Model for Community-Dwelling Elderly Aged >55 Years.Neuropsychiatric disease and treatment · 2022Article
- Predicting suicidal behavior in individuals with depression over 50 years of age: Evidence from the UK biobank.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Suicide poses a serious problem globally, especially among the elderly population. To tackle the issue, this study aimed to develop a model for predicting suicide by using machine learning based on the elderly population. To obtain a large sample, the study used the big data health screening cohort provided by the National Health Insurance Sharing Service. By applying a machine learning technique, a predictive model that comprehensively utilized various factors was developed to select the elderly aged > 65 years at risk of suicide. A total of 48,047 subjects were included in the analysis. Individuals who died by suicide were older, and the number of men was significantly greater. The suicide group had a more prominent history of depression, with the use of medicaments significantly higher. Specifically, the prescription of benzodiazepines alone was associated with a high suicide risk. Furthermore, body mass index, waist circumference, total cholesterol, and low-density lipoprotein level were lower in the suicide group. We developed a model for predicting suicide by using machine learning based on the elderly population. This suicide prediction model can satisfy the performance to some extent by employing only the medical service usage behavior without subjective reports.
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Registered trials
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.