Last Posted: Jul 11, 2019
- Leveraging Digital Health and Machine Learning Toward Reducing SuicideFrom Panacea to Practical Tool
J Torous et al, JAMA Psychiatry, July 10, 2019
- Association Between Parental Medical Claims for Opioid Prescriptions and Risk of Suicide Attempt by Their Children.
Brent David A et al. JAMA psychiatry 2019 May
- Feasibility and Acceptability of Using a Mobile Phone App for Characterizing Auditory Verbal Hallucinations in Adolescents With Early-Onset Psychosis: Exploratory Study.
Smelror Runar Elle et al. JMIR formative research 2019 May 3(2) e13882
- Using Machine Learning to Identify Suicide Risk: A Classification Tree Approach to Prospectively Identify Adolescent Suicide Attempters.
Hill Ryan M et al. Archives of suicide research : official journal of the International Academy for Suicide Research 2019 May 1-33
- Genetic and environmental sources of familial coaggregation of obsessive-compulsive disorder and suicidal behavior: a population-based birth cohort and family study.
Sidorchuk Anna, et al. Molecular psychiatry 2019 4 0.
- Familial Aggregation and Coaggregation of Suicide Attempts and Comorbid Mental Disorders in Adults.
Ballard Elizabeth D et al. JAMA psychiatry 2019 Mar
- Preventing Suicidal Behavior
CDC Public Health Grand Rounds, March 2019
- Machine learning in suicide science: Applications and ethics.
Linthicum Kathryn P et al. Behavioral sciences & the law 2019 Jan
- Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior.
Velupillai Sumithra et al. Frontiers in psychiatry 2019 1036
- Suicide and suicide behaviors: A review of transcriptomics and multiomics studies in psychiatric disorders.
Zhou Yi et al. Journal of neuroscience research 2018 Dec
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