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

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Machine Learning (1501) Artificial Intelligence (1421) Pediatrics (139) Screening and Early Diagnosis in Pediatrics (30)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44467, first published .
Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning–Based Text-Mining Approach

Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning–Based Text-Mining Approach

Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning–Based Text-Mining Approach

Authors of this article:

Danila Azzolina1 Author Orcid Image ;   Silvia Bressan2 Author Orcid Image ;   Giulia Lorenzoni3 Author Orcid Image ;   Giulia Andrea Baldan3 Author Orcid Image ;   Patrizia Bartolotta3 Author Orcid Image ;   Federico Scognamiglio3 Author Orcid Image ;   Andrea Francavilla3 Author Orcid Image ;   Corrado Lanera3 Author Orcid Image ;   Liviana Da Dalt2 Author Orcid Image ;   Dario Gregori3 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Zhang Z, Huang Y, Liu G, Yu W, Xie Q, Chen Z, Huang G, Wei J, Zhang H, Chen D, Du H. Development of machine learning-based predictors for early diagnosis of hepatocellular carcinoma. Scientific Reports 2024;14(1) View
  2. Lorenzoni G, Gregori D, Bressan S, Ocagli H, Azzolina D, Da Dalt L, Berchialla P. Use of a Large Language Model to Identify and Classify Injuries With Free-Text Emergency Department Data. JAMA Network Open 2024;7(5):e2413208 View