Ten-year prediction of suicide death using Cox regression and machine learning in a nationwide retrospective cohort study in South Korea

Journal of Affective Disorders

Volumn 231, Issue , 2018, Pages 8-14

  Choi, Soo Beom ^a,b   Lee, Wanhyung ^a,c   Yoon, Jin Ha ^a,c   Won, Jong Uk ^a,c   Kim, Deok Won ^a,b  

^a Yonsei University College of Medicine   (South Korea)

^b Yonsei University   (South Korea)

^c Workers' Health Center   (South Korea)

Author keywords

Cox regression; Deep learning; Suicide prediction; Support vector machine

Indexed keywords

ADOLESCENT; ADULT; AGED; ARTICLE; AUTOMUTILATION; COHORT ANALYSIS; CONTROLLED STUDY; DEEP NEURAL NETWORK; FEMALE; FOLLOW UP; HOUSEHOLD INCOME; HUMAN; ICD-10; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MEDICAL RECORD; NATIONAL HEALTH INSURANCE; PATTERN RECOGNITION; PREDICTION; PRIORITY JOURNAL; PROPORTIONAL HAZARDS MODEL; PUBLIC HEALTH INSURANCE; RETROSPECTIVE STUDY; SOUTH KOREA; SUICIDE; SUPPORT VECTOR MACHINE; AREA UNDER THE CURVE; ARTIFICIAL NEURAL NETWORK; FACTUAL DATABASE; HEALTH INSURANCE; MENTAL DISEASE; MIDDLE AGED; RISK FACTOR; STATISTICS AND NUMERICAL DATA; YOUNG ADULT;

ADULT; AREA UNDER CURVE; DATABASES, FACTUAL; FEMALE; HUMANS; INSURANCE, HEALTH; MACHINE LEARNING; MALE; MENTAL DISORDERS; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); PROPORTIONAL HAZARDS MODELS; REPUBLIC OF KOREA; RETROSPECTIVE STUDIES; RISK FACTORS; SUICIDE; YOUNG ADULT;

EID: 85041482472     PISSN: 01650327     EISSN: 15732517     Source Type: Journal    
DOI: 10.1016/j.jad.2018.01.019     Document Type: Article

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