Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45085, first published .
Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study

Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study

Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study

Journals

  1. Shih D, Wu Y, Wu T, Chang S, Shih M. Infodemiology of Influenza-like Illness: Utilizing Google Trends’ Big Data for Epidemic Surveillance. Journal of Clinical Medicine 2024;13(7):1946 View
  2. Han X, Yang J, Luo Y, Huo D, Yu X, Hu X, Xin L, Yang L, Xin H, Zhang T, Li Z, Yang W. Exploring the Lagged Correlation Between Baidu Index and Influenza-Like Illness — China, 2014–2019. China CDC Weekly 2024;6(26):629 View
  3. Zhang T, Yang L, Fan Z, Hu X, Yang J, Luo Y, Huo D, Yu X, Xin L, Han X, Shan J, Li Z, Yang W. Comparison Between Threshold Method and Artificial Intelligence Approaches for Early Warning of Respiratory Infectious Diseases — Weifang City, Shandong Province, China, 2020–2023. China CDC Weekly 2024;6(26):635 View
  4. Danchin A. Artificial intelligence‐based prediction of pathogen emergence and evolution in the world of synthetic biology. Microbial Biotechnology 2024;17(10) View
  5. Deng P, Xue C, Yang T, Zheng B, Liu W, Yang L, Fei Y. Epidemiological analysis of influenza vaccination coverage in Pudong New Area, Shanghai (2013-2023): Implications for influenza vaccination strategies. Human Vaccines & Immunotherapeutics 2024;20(1) View