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

Outbreak and Pandemic Preparedness and Management (1826) Clinical Informatics (1325) Public (e)Health, Digital Epidemiology and Public Health Informatics (1008) Surveillance Systems (514) Machine Learning (2076) Infectious Diseases (non-STD/STI) (1726) Use Cases in Human, Animal, and Zoonotic Communicable/Infectious Disease Surveillance (145)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59971, first published .
Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Authors of this article:

Ravikiran Keshavamurthy1, 2 Author Orcid Image ;   Karl T Pazdernik1, 3 Author Orcid Image ;   Colby Ham1 Author Orcid Image ;   Samuel Dixon1 Author Orcid Image ;   Samantha Erwin1 Author Orcid Image ;   Lauren E Charles1, 2 Author Orcid Image
Article Authors Cited by (1) Tweetations (1) Metrics

Journals

  1. Guma F. Analysis of influenza-like illness trends in Saudi Arabia: a comparative study of statistical and deep learning techniques. Osong Public Health and Research Perspectives 2025;16(3):270 View