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

Public (e)Health, Digital Epidemiology and Public Health Informatics (871) Infodemiology and Infoveillance (1468) Influenza and Influenza-Like-Illness (ILI) Surveillance (225) Infectious Diseases (non-STD/STI) (1659) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1089) Artificial Intelligence (1779) Machine Learning (1770) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (63)

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

Authors of this article:

Liuyang Yang1, 2 Author Orcid Image ;   Ting Zhang2 Author Orcid Image ;   Xuan Han2 Author Orcid Image ;   Jiao Yang2 Author Orcid Image ;   Yanxia Sun2 Author Orcid Image ;   Libing Ma2, 3 Author Orcid Image ;   Jialong Chen4 Author Orcid Image ;   Yanming Li4 Author Orcid Image ;   Shengjie Lai5 Author Orcid Image ;   Wei Li6 Author Orcid Image ;   Luzhao Feng2 Author Orcid Image ;   Weizhong Yang2 Author Orcid Image
Article Authors Cited by (9) Tweetations (3) Metrics

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
  6. Xiong X, Xiang L, Chang L, Wu I, Deng S. Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study. Journal of Medical Internet Research 2025;27:e66072 View
  7. Qi S, Tham J, Waheed M, Hashim N. From fear to facts: a multi-channel approach to information seeking amid influenza-like illness outbreaks. Frontiers in Public Health 2025;13 View
  8. Kim J, Jeong A, Jin J, Lee S, Yoon D, Kim S. Temporal Association Between ChatGPT-Generated Diarrhea Synonyms in Internet Search Queries and Emergency Department Visits for Diarrhea-Related Symptoms in South Korea: Exploratory Study. Journal of Medical Internet Research 2025;27:e65101 View

Conference Proceedings

  1. Kashmar N, Ozdemir D, Yousuf I, Dabboussi A, Saab A, Salem-Sokhn E, El Morr C. 2025 International Conference on Control, Automation, and Instrumentation (IC2AI). Enhancing Epidemic Early Warning Systems with Social Media Data View