Early identification of posttraumatic stress following military deployment: Application of machine learning methods to a prospective study of Danish soldiers

Journal of Affective Disorders

Volumn 184, Issue , 2015, Pages 170-175

  Karstoft, Karen Inge ^a   Statnikov, Alexander ^b   Andersen, Søren B ^a   Madsen, Trine ^a,c   Galatzer Levy, Isaac R ^b  

^a Research and Knowledge Centre   (Denmark)

^b NEW YORK UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

Machine learning; Military; Posttraumatic stress; Prediction; Prevention; Support vector machines

Indexed keywords

ADULT; AFGHANISTAN; ARTICLE; CONTROLLED STUDY; COPING BEHAVIOR; DANISH CITIZEN; EMOTION; FEMALE; HUMAN; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALE; MILITARY DEPLOYMENT; POSTTRAUMATIC STRESS DISORDER; PREDICTION; PRIORITY JOURNAL; PROSPECTIVE STUDY; RISK ASSESSMENT; SOLDIER; SUPPORT VECTOR MACHINE; SYMPTOM; THINKING; ALGORITHM; COHORT ANALYSIS; DENMARK; MACHINE LEARNING; PREDICTIVE VALUE; PSYCHOLOGY; WAR;

ADULT; AFGHAN CAMPAIGN 2001-; ALGORITHMS; COHORT STUDIES; DENMARK; EMOTIONS; FEMALE; HUMANS; LONGITUDINAL STUDIES; MACHINE LEARNING; MALE; MILITARY PERSONNEL; PREDICTIVE VALUE OF TESTS; PROSPECTIVE STUDIES; RESILIENCE, PSYCHOLOGICAL; RISK ASSESSMENT; STRESS DISORDERS, POST-TRAUMATIC; SUPPORT VECTOR MACHINE;

EID: 84934893196     PISSN: 01650327     EISSN: 15732517     Source Type: Journal    
DOI: 10.1016/j.jad.2015.05.057     Document Type: Article

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