ArticleFrontiers in psychiatry2018
Protecting Life While Preserving Liberty: Ethical Recommendations for Suicide Prevention With Artificial Intelligence.
Article in Frontiers in psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Structured data vs. unstructured data in machine learning prediction models for suicidal behaviors: A systematic review and meta-analysis.Frontiers in digital health · 2022Pooled it
- Use of Ecological Momentary Assessment to Study Suicidal Thoughts and Behavior: a Systematic Review.Current psychiatry reports · 2021Pooled it
- Machine Learning and Natural Language Processing in Mental Health: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Guiding Policymakers Toward Better AI Ethics Integration in Healthcare Regulation-Lessons from Singapore.Journal of clinical medicine · 2026Review
- AI in Mental Health: Transforming Diagnosis and Management of Depression and Anxiety.Health science reports · 2026Article
- Applications of Large Language Models in the Field of Suicide Prevention: Scoping Review.Journal of medical Internet research · 2025Article
- The Ethics of Risk Prediction for Psychosis and Suicide Attempt in Youth Mental Health.The Journal of pediatrics · 2023Review
- Identifying Predictors of Psychological Problems Among Adolescents With Congenital Heart Disease for Referral to Psychological Care: A Pilot Study.CJC pediatric and congenital heart disease · 2023Article
- Artificial intelligence assisted tools for the detection of anxiety and depression leading to suicidal ideation in adolescents: a review.Cognitive neurodynamics · 2022Review
- Workplace health surveillance and COVID-19: algorithmic health discrimination and cancer survivors.Journal of cancer survivorship : research and practice · 2022Article
- A Critical Review of Text Mining Applications for Suicide Research.Current epidemiology reports · 2022Review
- Risky business: a scoping review for communicating results of predictive models between providers and patients.JAMIA open · 2021Article
- Electronic Health Records and Machine Learning for Early Detection of Lung Cancer and Other Conditions: Thinking about the Path Ahead.American journal of respiratory and critical care medicine · 2021Article
- Information and Communication Technology Use in Suicide Prevention: Scoping Review.Journal of medical Internet research · 2021Article
- Stigma, biomarkers, and algorithmic bias: recommendations for precision behavioral health with artificial intelligence.JAMIA open · 2020Article
- Suicide prediction models: a critical review of recent research with recommendations for the way forward.Molecular psychiatry · 2020Review
- Prognostic models will be victims of their own success, unless….Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Precision Medicine and Suicide: an Opportunity for Digital Health.Current psychiatry reports · 2019Review
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.
Funding
Abstract
In the United States, suicide increased by 24% in the past 20 years, and suicide risk identification at point-of-care remains a cornerstone of the effort to curb this epidemic (1). As risk identification is difficult because of symptom under-reporting, timing, or lack of screening, healthcare systems rely increasingly on risk scoring and now artificial intelligence (AI) to assess risk. AI remains the science of solving problems and accomplishing tasks, through automated or computational means, that normally require human intelligence. This science is decades-old and includes traditional predictive statistics and machine learning. Only in the last few years has it been applied rigorously in suicide risk prediction and prevention. Applying AI in this context raises significant ethical concern, particularly in balancing beneficence and respecting personal autonomy. To navigate the ethical issues raised by suicide risk prediction, we provide recommendations in three areas-communication, consent, and controls-for both providers and researchers (2).
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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.