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

Foundations of AI (47) Artificial Intelligence (1421)

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 (4) Tweetations (7) Metrics

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  2. Akyon S, Akyon F, Camyar A, Hızlı F, Sari T, Hızlı Ş. Evaluating the Capabilities of Generative AI Tools in Understanding Medical Papers: Qualitative Study. JMIR Medical Informatics 2024;12:e59258 View
  3. Dorémus O, Russon D, Contrand B, Guerra-Adames A, Avalos-Fernandez M, Gil-Jardiné C, Lagarde E. Harnessing Moderate-Sized Language Models for Reliable Patient Data De-identification in Emergency Department Records: An Evaluation of Strategies and Performance (Preprint). JMIR AI 2024 View