Testing Suicide Risk Prediction Algorithms Using Phone Measurements With Patients in Acute Mental Health Settings: Feasibility Study

Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study

(2019) Chul-Hyun Cho et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

Reconciling modern machine-learning practice and the classical bias–variance trade-off

(2019) Mikhail Belkin et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Predicting Suicide Attempts and Suicide Deaths Following Outpatient Visits Using Electronic Health Records

(2018) Gregory E. Simon et al.   AMERICAN JOURNAL OF PSYCHIATRY

Digital phenotyping of suicidal thoughts

(2018) Evan M. Kleiman et al.   DEPRESSION AND ANXIETY

Smartphones, Sensors, and Machine Learning to Advance Real-Time Prediction and Interventions for Suicide Prevention: a Review of Current Progress and Next Steps

(2018) John Torous et al.   Current Psychiatry Reports

Rise of the machines? Machine learning approaches and mental health: opportunities and challenges

(2018) Paul A. Tiffin et al.   BRITISH JOURNAL OF PSYCHIATRY

Developing a practical suicide risk prediction model for targeting high-risk patients in the Veterans health Administration

(2017) Ronald C. Kessler et al.   INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH

Points of Significance: Principal component analysis

(2017) Jake Lever et al.   NATURE METHODS

Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research.

(2017) Joseph C. Franklin et al.   PSYCHOLOGICAL BULLETIN

New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices

(2017) J Torous et al.   Translational Psychiatry

Acute Mental Discomfort Associated with Suicide Behavior in a Clinical Sample of Patients with Affective Disorders: Ascertaining Critical Variables Using Artificial Intelligence Tools

(2017) Susana Morales et al.   Frontiers in Psychiatry

Identifying a clinical signature of suicidality among patients with mood disorders: A pilot study using a machine learning approach

(2016) Ives Cavalcante Passos et al.   JOURNAL OF AFFECTIVE DISORDERS

Suicide and suicidal behaviour

(2016) Gustavo Turecki et al.   LANCET

Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies

(2016) N Bidargaddi et al.   MOLECULAR PSYCHIATRY

Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports

(2016) R C Kessler et al.   MOLECULAR PSYCHIATRY

Harnessing Smartphone-Based Digital Phenotyping to Enhance Behavioral and Mental Health

(2016) Jukka-Pekka Onnela et al.   NEUROPSYCHOPHARMACOLOGY

Insomnia, Nightmares, and Chronotype as Markers of Risk for Severe Mental Illness: Results from a Student Population

(2016) Bryony Sheaves et al.   SLEEP

Insomnia, Nightmares, and Chronotype as Markers of Risk for Severe Mental Illness: Results from a Student Population

(2016) Bryony Sheaves et al.   SLEEP

A Systematic Assessment of Smartphone Tools for Suicide Prevention

(2016) Mark Erik Larsen et al.   PLoS One

Self-injurious thoughts and behaviors as risk factors for future suicide ideation, attempts, and death: a meta-analysis of longitudinal studies

(2015) J. D. Ribeiro et al.   PSYCHOLOGICAL MEDICINE

Predicting Suicides After Psychiatric Hospitalization in US Army Soldiers

(2015) Ronald C. Kessler et al.   JAMA Psychiatry

Suicidal process, suicidal communication and psychosocial situation of young suicide attempters in a rural Vietnamese community

(2015) DANUTA WASSERMAN et al.   World Psychiatry

Predicting the Risk of Suicide by Analyzing the Text of Clinical Notes

(2014) Chris Poulin et al.   PLoS One

Social Media and Suicide: A Public Health Perspective

(2012) David D. Luxton et al.   AMERICAN JOURNAL OF PUBLIC HEALTH

Sample size planning for classification models

(2012) Claudia Beleites et al.   ANALYTICA CHIMICA ACTA

Predicting sample size required for classification performance

(2012) Rosa L Figueroa et al.   BMC Medical Informatics and Decision Making

Suicide attempters classification: Toward predictive models of suicidal behavior

(2012) David Delgado-Gomez et al.   NEUROCOMPUTING

Psychiatric Disorders and Sleep

(2012) Andrew D. Krystal   NEUROLOGIC CLINICS

Infodemiology and Infoveillance

(2011) Gunther Eysenbach   AMERICAN JOURNAL OF PREVENTIVE MEDICINE

The Columbia–Suicide Severity Rating Scale: Initial Validity and Internal Consistency Findings From Three Multisite Studies With Adolescents and Adults

(2011) Kelly Posner et al.   AMERICAN JOURNAL OF PSYCHIATRY

Sleep problems outperform depression and hopelessness as cross-sectional and longitudinal predictors of suicidal ideation and behavior in young adults in the military

(2011) Jessica D. Ribeiro et al.   JOURNAL OF AFFECTIVE DISORDERS

Infodemiology and Infoveillance: Framework for an Emerging Set of Public Health Informatics Methods to Analyze Search, Communication and Publication Behavior on the Internet

(2009) Gunther Eysenbach   JOURNAL OF MEDICAL INTERNET RESEARCH

Ecological Momentary Assessment

(2007) Saul Shiffman et al.   Annual Review of Clinical Psychology