Identifying and Predicting Intentional Self-Harm in Electronic Health Record Clinical Notes: Deep Learning Approach

Assessment and Management of Patients at Risk for Suicide: Synopsis of the 2019 U.S. Department of Veterans Affairs and U.S. Department of Defense Clinical Practice Guidelines

(2019) James Sall et al.   ANNALS OF INTERNAL MEDICINE

Automated detection of altered mental status in emergency department clinical notes: a deep learning approach

(2019) Jihad S. Obeid et al.   BMC Medical Informatics and Decision Making

Screening pregnant women for suicidal behavior in electronic medical records: diagnostic codes vs. clinical notes processed by natural language processing

(2018) Qiu-Yue Zhong et al.   BMC Medical Informatics and Decision Making

Identifying Suicide Ideation and Suicidal Attempts in a Psychiatric Clinical Research Database using Natural Language Processing

(2018) Andrea C. Fernandes et al.   Scientific Reports

Serious Suicide Attempts: Systematic Review of Psychological Risk Factors

(2018) Yari Gvion et al.   Frontiers in Psychiatry

Extracting psychiatric stressors for suicide from social media using deep learning

(2018) Jingcheng Du et al.   BMC Medical Informatics and Decision Making

The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review

(2018) Taylor A. Burke et al.   JOURNAL OF AFFECTIVE DISORDERS

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

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

Instruments for the assessment of suicide risk: A systematic review evaluating the certainty of the evidence

(2017) Bo Runeson et al.   PLoS One

Suicide, Suicide Attempts, and Suicidal Ideation

(2016) E. David Klonsky et al.   Annual Review of Clinical Psychology

Predicting suicide following self-harm: systematic review of risk factors and risk scales

(2016) Melissa K. Y. Chan et al.   BRITISH JOURNAL OF PSYCHIATRY

Use of emergency department electronic medical records for automated epidemiological surveillance of suicide attempts: a French pilot study

(2016) Marie-Hélène Metzger et al.   INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH

Computerized Adaptive Test vs. decision trees: Development of a support decision system to identify suicidal behavior

(2016) D. Delgado-Gomez et al.   JOURNAL OF AFFECTIVE DISORDERS

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

(2016) R C Kessler et al.   MOLECULAR PSYCHIATRY

Improving Prediction of Suicide and Accidental Death After Discharge From General Hospitals With Natural Language Processing

(2016) Thomas H. McCoy et al.   JAMA Psychiatry

Deep learning

(2015) Yann LeCun et al.   NATURE

Suicide risk assessment and intervention in people with mental illness

(2015) J. M. Bolton et al.   BMJ-British Medical Journal

Suicide risk assessment and intervention in people with mental illness

(2015) J. M. Bolton et al.   BMJ-British Medical Journal

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

(2014) Chris Poulin et al.   PLoS One

Risk Factors for Repetition of Self-Harm: A Systematic Review of Prospective Hospital-Based Studies

(2014) Celine Larkin et al.   PLoS One

Distinguishing the relevant features of frequent suicide attempters

(2010) Jorge Lopez-Castroman et al.   JOURNAL OF PSYCHIATRIC RESEARCH

Classification Trees Distinguish Suicide Attempters in Major Psychiatric Disorders

(2009) J. John Mann et al.   JOURNAL OF CLINICAL PSYCHIATRY

Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support

(2008) Paul A. Harris et al.   JOURNAL OF BIOMEDICAL INFORMATICS