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

Infodemiology and Infoveillance (1269) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552) Influenza and Influenza-Like-Illness (ILI) Surveillance (203) Innovative Methods in Public Health and Surveillance (305) Memory (42)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42519, first published .
Long Short-term Memory–Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation

Long Short-term Memory–Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation

Long Short-term Memory–Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation

Authors of this article:

Maria Athanasiou1 Author Orcid Image ;   Georgios Fragkozidis1 Author Orcid Image ;   Konstantia Zarkogianni1 Author Orcid Image ;   Konstantina S Nikita1 Author Orcid Image
Article Authors Cited by (9) Tweetations (5) Metrics

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  1. Xue H, Zhang L, Liang H, Kuang L, Han H, Yang X, Guo L. Influenza trend prediction method combining Baidu index and support vector regression based on an improved particle swarm optimization algorithm. AIMS Mathematics 2023;8(11):25528 View
  2. Zarkogianni K, Dervakos E, Filandrianos G, Ganitidis T, Gkatzou V, Sakagianni A, Raghavendra R, Max Nikias C, Stamou G, Nikita K. The smarty4covid dataset and knowledge base as a framework for interpretable physiological audio data analysis. Scientific Data 2023;10(1) View
  3. Varela-Lasheras I, Perfeito L, Mesquita S, Gonçalves-Sá J, McGinnis R. The effects of weather and mobility on respiratory viruses dynamics before and during the COVID-19 pandemic in the USA and Canada. PLOS Digital Health 2023;2(12):e0000405 View
  4. Chhabra A, Singh S, Sharma A, Kumar S, Gupta B, Arya V, Chui K. Sustainable and intelligent time-series models for epidemic disease forecasting and analysis. Sustainable Technology and Entrepreneurship 2024;3(2):100064 View
  5. Oh G. Exploring Long Short Term Memory Algorithms for Low Energy Data Aggregation. Journal of Machine and Computing 2024:71 View
  6. Dai Z, Liu S, Liu C. Predict the prevalence and incidence of Parkinson’s disease using fractal interpolation-LSTM model. Chaos: An Interdisciplinary Journal of Nonlinear Science 2024;34(5) View
  7. Chen Q, Zheng X, Shi H, Zhou Q, Hu H, Sun M, Xu Y, Zhang X. Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models. BMC Public Health 2024;24(1) View
  8. Shao J, Pan Y, Kou W, Feng H, Zhao Y, Zhou K, Zhong S. Generalization of a Deep Learning Model for Continuous Glucose Monitoring–Based Hypoglycemia Prediction: Algorithm Development and Validation Study. JMIR Medical Informatics 2024;12:e56909 View