A machine-learning prediction model to identify risk of firearm injury using electronic health records data
Our model can support more targeted screening in healthcare settings, resulting in improved efficiency of firearm injury risk assessment and prevention efforts.
Authors
- Corinna Koebnick (ORCID: https://orcid.org/0000-0001-8274-0309)
- Margo A. Sidell (ORCID: https://orcid.org/0000-0001-7963-4505)
- Claudia Nau (ORCID: https://orcid.org/0000-0002-0373-2560)
- Fagen Xie (ORCID: https://orcid.org/0000-0002-1565-0490)
- Rulin C. Hechter (ORCID: https://orcid.org/0000-0001-8684-6506)
- Hui Cynthia Zhou (ORCID: https://orcid.org/0000-0002-6491-7745)
- Sonya Negriff (ORCID: https://orcid.org/0000-0002-1660-6301)
- Richard Contreras
- Deborah Ling Grant
Institutions
- Kaiser Permanente (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2024-09-04
- DOI
- https://doi.org/10.1093/jamia/ocae222
- Citations
- 2
- Primary Topic
- Gun Ownership and Violence Research
- Type
- article
- Field-Weighted Citation Impact
- 1.06
Funders
- Kaiser Permanente