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

Applications of AI (104) Artificial Intelligence (1421) Foundations of AI (47)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54449, first published .
Near Real-Time Syndromic Surveillance of Emergency Department Triage Texts Using Natural Language Processing: Case Study in Febrile Convulsion Detection

Near Real-Time Syndromic Surveillance of Emergency Department Triage Texts Using Natural Language Processing: Case Study in Febrile Convulsion Detection

Near Real-Time Syndromic Surveillance of Emergency Department Triage Texts Using Natural Language Processing: Case Study in Febrile Convulsion Detection

Authors of this article:

Sedigh Khademi1, 2 Author Orcid Image ;   Christopher Palmer2 Author Orcid Image ;   Muhammad Javed2 Author Orcid Image ;   Gerardo Luis Dimaguila1, 2, 3 Author Orcid Image ;   Hazel Clothier1, 2, 3, 4 Author Orcid Image ;   Jim Buttery1, 2, 3, 5 Author Orcid Image ;   Jim Black4, 6 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Sedigh Khademi   1, 2 , PhD ;   Christopher Palmer   2 , Dip Bus Comp ;   Muhammad Javed   2 , PhD ;   Gerardo Luis Dimaguila   1, 2, 3 , PhD ;   Hazel Clothier   1, 2, 3, 4 , PhD ;   Jim Buttery   1, 2, 3, 5 , PhD, Prof Dr Med ;   Jim Black   4, 6 , MD, PhD

1 Department of Paediatrics, University of Melbourne, Melbourne, Australia

2 Health Informatics Group, Centre for Health Analytics, Melbourne Children's Campus, Melbourne, Australia

3 SAEFVIC, Murdoch Children’s Research Institute, Melbourne, Australia

4 Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia

5 Infectious Diseases, Royal Children’s Hospital, Melbourne, Australia

6 Department of Health, State Government of Victoria, Melbourne, Australia

Corresponding Author: