Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities.
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| Title: | Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities. |
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| Authors: | Choi D; Department of Computer Science and Engineering, Incheon National University, Incheon, South Korea., Sumner SA; Office of Strategy and Innovation, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia., Holland KM; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia., Draper J; National Suicide Prevention Lifeline, New York, New York., Murphy S; National Suicide Prevention Lifeline, New York, New York., Bowen DA; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia., Zwald M; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia., Wang J; Division of Violence Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia., Law R; National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia., Taylor J; School of Interactive Computing, Georgia Institute of Technology, Atlanta., Konjeti C; School of Interactive Computing, Georgia Institute of Technology, Atlanta., De Choudhury M; School of Interactive Computing, Georgia Institute of Technology, Atlanta. |
| Source: | JAMA network open [JAMA Netw Open] 2020 Dec 01; Vol. 3 (12), pp. e2030932. Date of Electronic Publication: 2020 Dec 01. |
| Publication Type: | Journal Article; Research Support, U.S. Gov't, P.H.S. |
| Journal Info: | Publisher: American Medical Association Country of Publication: United States NLM ID: 101729235 Publication Model: Electronic Cited Medium: Internet ISSN: 2574-3805 (Electronic) Linking ISSN: 25743805 NLM ISO Abbreviation: JAMA Netw Open Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2574-3805 |
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| DOI: | 10.1001/jamanetworkopen.2020.30932 |
