Predicting death by suicide using administrative health care system data: Can recurrent neural network, one-dimensional convolutional neural network, and gradient boosted trees models improve prediction performance?

Journal: Journal of affective disorders

Published Date: Dec 14, 2019

BACKGROUND: Suicide is a leading cause of death, particularly in younger persons, and this results in tremendous years of life lost.

Michael Sanderson

Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, TRW, 4th Floor, Room 4D66, 3280 Hospital Drive NW, Calgary, Alberta, Canada. Electronic address: michael.sanderson@gov.ab.ca.
Andrew Gm Bulloch

Hotchkiss Brain Institute, Department of Psychiatry, Cumming School of Medicine, University of Calgary, TRW, 4th Floor, Room 4D67, 3280 Hospital Drive NW, Calgary, Alberta, Canada.
JianLi Wang

School of Epidemiology, Public Health and Preventive Medicine, Department of Psychiatry, Faculty of Medicine, University of Ottawa, Royal Ottawa Mental Health Centre, 1145 Carling Avenue, Ottawa, Ontario, Canada.
Tyler Williamson

Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, TRW, 3rd Floor, Room 3D15, 3280 Hospital Drive NW, Calgary, Alberta, Canada.
Scott B Patten

Department of Community Health Sciences, Department of Psychiatry, Cumming School of Medicine, University of Calgary, TRW, 4th Floor, Room 4D66, 3280 Hospital Drive NW, Calgary, Alberta, Canada.

Delivery of Health Care Humans Machine Learning Neural Networks, Computer Suicide Trees

View on PubMed Access via DOI PubMed (32056739)