Accessibility settings

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54449, first published .
Child with a fever being comforted by a parent's hand on their forehead

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

Journals

  1. Berikol G, Kanbakan A, Ilhan B, Doğanay F. Mapping artificial intelligence models in emergency medicine: A scoping review on artificial intelligence performance in emergency care and education. Turkish Journal of Emergency Medicine 2025;25(2):67 View
  2. Gomes Ferreira A, Anžel A, Ullrich A, Hattab G. Advocating the potential of artificial intelligence for syndrome discovery in syndromic surveillance systems: A scoping review. iScience 2026;29(3):115103 View
  3. Diaz L, Ling C, Beaudoin M. Baseline Corpus Construction and Proof-of-concept Experiments for AI/ML-Enabled Syndromic Surveillance. Military Medicine 2026;191(Supplement_1):528 View
  4. Brown N, Taylor E, Wilson J, Scott O. Contrastive Learning with Prototypical Networks for Few-Shot Detection of Emerging Infectious Disease Outbreaks from Emergency Department Chief Complaints and Triage Notes. Journal of Artificial Intelligence for Healthcare Systems 2026;5(2) View

Books/Policy Documents

  1. Khademi S, Palmer C, Javed M, Clothier H, Buttery J, Dimaguila G, Black J. Data Science and Machine Learning. View
  2. Branda F, Ciccozzi M, Scarpa F. AI for Epidemic Preparedness. View