Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.
Authors
Noam G. Newberger (ORCID: https://orcid.org/0000-0001-5310-0839)
Clara E Roth (ORCID: https://orcid.org/0000-0002-0357-6668)
Frank Meng (ORCID: https://orcid.org/0000-0002-3065-1619)
Daniel Chen (ORCID: https://orcid.org/0000-0001-6672-6814)
Alexis Sarpong
Rebecca Hall (ORCID: https://orcid.org/0000-0002-1786-7984)
Anne N. Banducci (ORCID: https://orcid.org/0000-0003-1213-7998)
Nicholas A. Livingston (ORCID: https://orcid.org/0000-0001-5671-3200)
Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.
Noam G. Newberger, Clara E Roth, Frank Meng, Daniel Chen et al.
Citations
1 citations
Journal
Journal of Psychopathology and Clinical Science
Topics
Machine Learning in Healthcare
Field-Weighted Citation Impact (FWCI)
2.48
article
Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.
Noam G. Newberger, Clara E Roth, Frank Meng, Daniel Chen, Alexis Sarpong, Rebecca Hall, Anne N. Banducci, Nicholas A. Livingston, Zig Hinds, Lauren B. Loeffel, Miriam Ting, Amar Mandavia, Jennifer R. Fonda, Michael Davenport, Brittany Mathes-Winnicki
article en
1 citations
Abstract
No abstract available for this paper.
Publication Tag
Journal of Psychopathology and Clinical ScienceVol. 134(4)
Institutions
Boston University (US), VA Boston Healthcare System (US), National Center for PTSD (US), Boston VA Research Institute (US), Minneapolis VA Health Care System (US)
Funders
U.S. Department of Veterans Affairs, Patient-Centered Outcomes Research Institute