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

Natural Language Processing (29) Artificial Intelligence (1216) Machine Learning (1401) Clinical Informatics (919) Natural Language Processing (650) Machine Learning (52)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40843, first published .
Deep Learning Transformer Models for Building a Comprehensive and Real-time Trauma Observatory: Development and Validation Study

Deep Learning Transformer Models for Building a Comprehensive and Real-time Trauma Observatory: Development and Validation Study

Deep Learning Transformer Models for Building a Comprehensive and Real-time Trauma Observatory: Development and Validation Study

Authors of this article:

Gabrielle Chenais1 Author Orcid Image ;   Cédric Gil-Jardiné1, 2 Author Orcid Image ;   Hélène Touchais1 Author Orcid Image ;   Marta Avalos Fernandez1, 3 Author Orcid Image ;   Benjamin Contrand1 Author Orcid Image ;   Eric Tellier1, 2 Author Orcid Image ;   Xavier Combes2 Author Orcid Image ;   Loick Bourdois1 Author Orcid Image ;   Philippe Revel2 Author Orcid Image ;   Emmanuel Lagarde1 Author Orcid Image
Article Authors Cited by (1) Tweetations (7) Metrics

Journals

  1. Preiksaitis C, Ashenburg N, Bunney G, Chu A, Kabeer R, Riley F, Ribeira R, Rose C. The Role of Large Language Models in Transforming Emergency Medicine: Scoping Review. JMIR Medical Informatics 2024;12:e53787 View