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

Surveillance Systems (427) Infodemiology and Infoveillance (1269) Machine Learning (1370) Infectious Diseases (non-STD/STI) (1478) Influenza and Influenza-Like-Illness (ILI) Surveillance (203) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010)

Published on in Vol 4, No 4 (2018): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11361, first published .
Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods: Comparison Study

Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods: Comparison Study

Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods: Comparison Study

Authors of this article:

Canelle Poirier1, 2 Author Orcid Image ;   Audrey Lavenu3 Author Orcid Image ;   Valérie Bertaud1, 2, 4 Author Orcid Image ;   Boris Campillo-Gimenez2, 5 Author Orcid Image ;   Emmanuel Chazard6, 7 Author Orcid Image ;   Marc Cuggia1, 2, 4 Author Orcid Image ;   Guillaume Bouzillé1, 2, 4 Author Orcid Image
Article Authors Cited by (18) Tweetations (10) Metrics

Journals

  1. Darwish A, Rahhal Y, Jafar A. A comparative study on predicting influenza outbreaks using different feature spaces: application of influenza-like illness data from Early Warning Alert and Response System in Syria. BMC Research Notes 2020;13(1) View
  2. Ribeiro M, Mariani V, Coelho L. Multi-step ahead meningitis case forecasting based on decomposition and multi-objective optimization methods. Journal of Biomedical Informatics 2020;111:103575 View
  3. Mavragani A, Ochoa G. Google Trends in Infodemiology and Infoveillance: Methodology Framework. JMIR Public Health and Surveillance 2019;5(2):e13439 View
  4. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  5. Cheng H, Wu Y, Lin M, Liu Y, Tsai Y, Wu J, Pan K, Ke C, Chen C, Liu D, Lin I, Chuang J. Applying Machine Learning Models with An Ensemble Approach for Accurate Real-Time Influenza Forecasting in Taiwan: Development and Validation Study. Journal of Medical Internet Research 2020;22(8):e15394 View
  6. Goldberg M, Zins M. Le Health Data Hub (suite). médecine/sciences 2021;37(3):271 View
  7. Yang L, Zhang T, Glynn P, Scheinker D. The development and deployment of a model for hospital-level COVID-19 associated patient demand intervals from consistent estimators (DICE). Health Care Management Science 2021;24(2):375 View
  8. Zins M, Cuggia M, Goldberg M. Les données de santé en France. médecine/sciences 2021;37(2):179 View
  9. Lv H, Yang X, Wang B, Wang S, Du X, Tan Q, Hao Z, Liu Y, Yan J, Xia Y. Machine Learning–Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study. Journal of Medical Internet Research 2021;23(4):e24996 View
  10. Poirier C, Hswen Y, Bouzillé G, Cuggia M, Lavenu A, Brownstein J, Brewer T, Santillana M, Chong K. Influenza forecasting for French regions combining EHR, web and climatic data sources with a machine learning ensemble approach. PLOS ONE 2021;16(5):e0250890 View
  11. Heaton M, Ingersoll C, Berrett C, Hartman B, Sloan C. A Bayesian approach to real-time spatiotemporal prediction systems for bronchiolitis. Spatial and Spatio-temporal Epidemiology 2021;38:100434 View
  12. Aiken E, Nguyen A, Viboud C, Santillana M. Toward the use of neural networks for influenza prediction at multiple spatial resolutions. Science Advances 2021;7(25) View
  13. Snider B, McBean E, Yawney J, Gadsden S, Patel B. Identification of Variable Importance for Predictions of Mortality From COVID-19 Using AI Models for Ontario, Canada. Frontiers in Public Health 2021;9 View
  14. Poirier C, Bouzillé G, Bertaud V, Cuggia M, Santillana M, Lavenu A. Gastroenteritis Forecasting Assessing the Use of Web and Electronic Health Record Data With a Linear and a Nonlinear Approach: Comparison Study. JMIR Public Health and Surveillance 2023;9:e34982 View
  15. Zhu J, Xu Y, Yu G, Gao J, Liu Y, Cheng D, Song C, Chen J, Pei T, Shah Z. A LASSO-Based Prediction Model for Child Influenza Epidemics: A Case Study of Shanghai, China. Mathematical Problems in Engineering 2022;2022:1 View
  16. Olukanmi S, Nelwamondo F, Nwulu N. Utilizing Google Search Data With Deep Learning, Machine Learning and Time Series Modeling to Forecast Influenza-Like Illnesses in South Africa. IEEE Access 2021;9:126822 View
  17. Zhang L, Li M, Zhi C, Zhu M, Ma H. Identification of Early Warning Signals of Infectious Diseases in Hospitals by Integrating Clinical Treatment and Disease Prevention. Current Medical Science 2024;44(2):273 View
  18. Castro Blanco E, Dalmau Llorca M, Aguilar Martín C, Carrasco-Querol N, Gonçalves A, Hernández Rojas Z, Coma E, Fernández-Sáez J. A Predictive Model of the Start of Annual Influenza Epidemics. Microorganisms 2024;12(7):1257 View