This paper is in the following e-collection/theme issue:

Depression and Mood Disorders; Suicide Prevention (1341) Short Paper (23) Violence including Domestic Violence/Abuse (115) Machine Learning (1434) Machine Learning (39) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (31)

Published on in Vol 10 (2023)

This is a member publication of University of Washington

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49359, first published .
Identifying Rare Circumstances Preceding Female Firearm Suicides: Validating A Large Language Model Approach

Identifying Rare Circumstances Preceding Female Firearm Suicides: Validating A Large Language Model Approach

Identifying Rare Circumstances Preceding Female Firearm Suicides: Validating A Large Language Model Approach

Authors of this article:

Weipeng Zhou1 Author Orcid Image ;   Laura C Prater2, 3 Author Orcid Image ;   Evan V Goldstein4 Author Orcid Image ;   Stephen J Mooney5 Author Orcid Image
Article Authors Cited by (3) Tweetations (8) Metrics

Journals

  1. Zhu J, Cukier M, Richardson J. Nutrition facts, drug facts, and model facts: putting AI ethics into practice in gun violence research. Journal of the American Medical Informatics Association 2024;31(10):2414 View
  2. Burford K, Itzkowitz N, Ortega A, Teitler J, Rundle A. Use of Generative AI to Identify Helmet Status Among Patients With Micromobility-Related Injuries From Unstructured Clinical Notes. JAMA Network Open 2024;7(8):e2425981 View
  3. Burford K, Itzkowitz N, Rundle A, DiMaggio C, Mooney S. The Burden of Injuries Associated With E-Bikes, Powered Scooters, Hoverboards, and Bicycles in the United States: 2019‒2022. American Journal of Public Health 2024:e1 View