Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44238, first published .
Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation

Journals

  1. Zhang T, Yang L, Han X, Fan G, Qian J, Hu X, Lai S, Li Z, Liu Z, Feng L, Yang W. Methods on COVID-19 Epidemic Curve Estimation During Emergency Based on Baidu Search Engine and ILI Traditional Surveillance in Beijing, China. Engineering 2023;31:112 View
  2. Hongliang G, Zhiyao Z, Ahmadianfar I, Escorcia-Gutierrez J, Aljehane N, Li C. Multi-step influenza forecasting through singular value decomposition and kernel ridge regression with MARCOS-guided gradient-based optimization. Computers in Biology and Medicine 2024;169:107888 View
  3. McClymont H, Lambert S, Barr I, Vardoulakis S, Bambrick H, Hu W. Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic. Journal of Epidemiology and Global Health 2024;14(3):645 View
  4. El Morr C, Ozdemir D, Asdaah Y, Saab A, El-Lahib Y, Sokhn E. AI-based epidemic and pandemic early warning systems: A systematic scoping review. Health Informatics Journal 2024;30(3) View
  5. Zeng Z, Jia L, Zheng J, Nian X, Zhang Z, Chen L, Chen X, Li Y, Zhang J. Molecular epidemiology and vaccine compatibility analysis of seasonal influenza A viruses in the context of COVID‐19 epidemic in Wuhan, China. Journal of Medical Virology 2024;96(10) View