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

Thomas H. McCoy | Zendy; Víctor M. Castro | Zendy; Ashlee M Roberson | Zendy; Leslie A. Snapper | Zendy; Roy H. Perlis | Zendy

Open Access

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

Author(s) -

Thomas H. McCoy,

Víctor M. Castro,

Ashlee M Roberson,

Leslie A. Snapper,

Roy H. Perlis

Publication year - 2016

Publication title -

jama psychiatry

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.531

H-Index - 365

eISSN - 2168-6238

pISSN - 2168-622X

DOI - 10.1001/jamapsychiatry.2016.2172

Subject(s) - medicine , poison control , retrospective cohort study , hazard ratio , cohort , injury prevention , medical record , suicide prevention , suicide attempt , occupational safety and health , cause of death , emergency medicine , demography , medical emergency , surgery , confidence interval , disease , pathology , sociology

Suicide represents the 10th leading cause of death across age groups in the United States (12.6 cases per 100 000) and remains challenging to predict. While many individuals who die by suicide are seen by physicians before their attempt, they may not seek psychiatric care.

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