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

Clinical Information and Decision Making (1915) Influenza and Influenza-Like-Illness (ILI) Surveillance (237) Machine Learning (2076) Artificial Intelligence (2129) Infectious Diseases (non-STD/STI) (1726)

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

Authors of this article:

Liuyang Yang1, 2 Author Orcid Image ;   Gang Li3 Author Orcid Image ;   Jin Yang2 Author Orcid Image ;   Ting Zhang2 Author Orcid Image ;   Jing Du3 Author Orcid Image ;   Tian Liu4 Author Orcid Image ;   Xingxing Zhang2 Author Orcid Image ;   Xuan Han2 Author Orcid Image ;   Wei Li5 Author Orcid Image ;   Libing Ma2, 6 Author Orcid Image ;   Luzhao Feng2 Author Orcid Image ;   Weizhong Yang2 Author Orcid Image
Article Authors Cited by (23) Tweetations (4) Metrics

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
  6. Xu D, Chan W, Haron H, Nies H, Moorthy K. From COVID-19 to monkeypox: a novel predictive model for emerging infectious diseases. BioData Mining 2024;17(1) View
  7. Dangi R, Sharma A, Vageriya V. Transforming Healthcare in Low‐Resource Settings With Artificial Intelligence: Recent Developments and Outcomes. Public Health Nursing 2025;42(2):1017 View
  8. Dhaked D, Sharma O, Gopal Y, Gopal R. Prediction of dengue patients using deep learning methods amid complex weather conditions in Jaipur, India. Discover Public Health 2025;22(1) View
  9. Liu M, Liu Y, Liu J. Machine Learning for Infectious Disease Risk Prediction: A Survey. ACM Computing Surveys 2025;57(8):1 View
  10. Adugna A, Abebaw D, Abebaw A, Jemal M. Deep learning architectures for influenza dynamics and treatment optimization: a comprehensive review. Frontiers in Artificial Intelligence 2025;8 View
  11. Yang X, Wang H, Lu H. Hotspots and Trends in Research on Early Warning of Infectious Diseases: A Bibliometric Analysis Using CiteSpace. Healthcare 2025;13(11):1293 View
  12. Li J, Yan X, Chu X, Zhang Y, Liu G, Li L, Li Y, Dong X, Mei Z, Liu Z, Yuan J, Sun X, Cao C. A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis. Journal of Medical Internet Research 2025;27:e71786 View
  13. Chen Y, Bo Y. AI-driven early detection of severe influenza in Jiangsu, China: a deep learning model validated through the design of multi-center clinical trials and prospective real-world deployment. Frontiers in Public Health 2025;13 View
  14. Adeoye A, Onifade I, Bayode M, Ariyibi I, Akangbe B, Akomolafe O, Ajisafe T, Hossain D, Owoeye O. Artificial intelligence and computational methods for modelling and forecasting influenza and influenza-like illness: a scoping review. Beni-Suef University Journal of Basic and Applied Sciences 2025;14(1) View
  15. Shen R, Xu X, Li Y, Sun Y, Xu Y, Duan Y, Liu X, Feng L. Enhancing spatiotemporal influenza prediction in China: a multi-output least absolute shrinkage and selection operator machine learning model integrating web-based search data. Intelligent Medicine 2025 View
  16. Safari M, Zali A, Hatami H, Jajin E, Akhlaghdoust M. Predicting Infectious Disease Incidence After Flooding Using Artificial Intelligence Models: A Retrospective Pre–Post Cohort Study Using Routinely Collected EHR Data. Health Science Reports 2025;8(11) View
  17. Gautam A, Raza Z, Lapina M, Babenko M. Attention-Driven Deep Learning for News-Based Prediction of Disease Outbreaks. Big Data and Cognitive Computing 2025;9(11):291 View
  18. Zhang T, Liu J. Impact of climate change on infectious disease transmission: a CiteSpace- and VOSviewer- based visualization of enteric, respiratory and vector-borne infectious disease studies. Frontiers in Climate 2025;7 View

Books/Policy Documents

  1. Lasaraiya S, Zenian S, Hasim R, Ashaari A, Uden L. Applied Neural Networks in the AI Era. View
  2. Lasaraiya S, Zenian S, Mat Hasim R, Ashaari A. Learning Technology for Education Challenges. View

Conference Proceedings

  1. Abd Rahim M, Yakub F, Omar M, Abd Ghani R, Dhamanti I, Sivakumar S. 2023 IEEE 2nd National Biomedical Engineering Conference (NBEC). Prediction of Influenza A Cases in Tropical Climate Country using Deep Learning Model View
  2. Wen Z, Jiang Z, Nie Y. 2023 IEEE 3rd International Conference on Data Science and Computer Application (ICDSCA). Wordle Distribution Prediction Model Based on Random Forest View
  3. 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