Influenza Forecasting with Google Flu Trends

Citations

Cited by:

1. Jichang Dong & Wei Dai & Ying Liu & Lean Yu & Jie Wang, 2019. "Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1605-1629, September.
2. Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
   • Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," MPRA Paper 102315, University Library of Munich, Germany.
3. Mansour Ebrahimi & Parisa Aghagolzadeh & Narges Shamabadi & Ahmad Tahmasebi & Mohammed Alsharifi & David L Adelson & Farhid Hemmatzadeh & Esmaeil Ebrahimie, 2014. "Understanding the Underlying Mechanism of HA-Subtyping in the Level of Physic-Chemical Characteristics of Protein," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-14, May.
4. Logan C Brooks & David C Farrow & Sangwon Hyun & Ryan J Tibshirani & Roni Rosenfeld, 2018. "Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions," PLOS Computational Biology, Public Library of Science, vol. 14(6), pages 1-29, June.
5. Feng Dong & Shengnan Zhang & Jiao Zhu & Jiaojiao Sun, 2021. "The Impact of the Integrated Development of AI and Energy Industry on Regional Energy Industry: A Case of China," IJERPH, MDPI, vol. 18(17), pages 1-24, August.
6. Symitsi, Efthymia & Markellos, Raphael N. & Mantrala, Murali K., 2022. "Keyword portfolio optimization in paid search advertising," European Journal of Operational Research, Elsevier, vol. 303(2), pages 767-778.
7. Martina Halouskov'a & Daniel Stav{s}ek & Mat'uv{s} Horv'ath, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Papers 2205.05985, arXiv.org, revised Aug 2022.
8. Baek, Changryong & Davis, Richard A. & Pipiras, Vladas, 2017. "Sparse seasonal and periodic vector autoregressive modeling," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 103-126.
9. Zeynep Ertem & Dorrie Raymond & Lauren Ancel Meyers, 2018. "Optimal multi-source forecasting of seasonal influenza," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-16, September.
10. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
11. Victor Olsavszky & Mihnea Dosius & Cristian Vladescu & Johannes Benecke, 2020. "Time Series Analysis and Forecasting with Automated Machine Learning on a National ICD-10 Database," IJERPH, MDPI, vol. 17(14), pages 1-17, July.
12. Linying Yang & Teng Zhang & Peter Glynn & David Scheinker, 2021. "The development and deployment of a model for hospital-level COVID-19 associated patient demand intervals from consistent estimators (DICE)," Health Care Management Science, Springer, vol. 24(2), pages 375-401, June.
13. Jose L Herrera & Ravi Srinivasan & John S Brownstein & Alison P Galvani & Lauren Ancel Meyers, 2016. "Disease Surveillance on Complex Social Networks," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-16, July.
14. Sangwon Chae & Sungjun Kwon & Donghyun Lee, 2018. "Predicting Infectious Disease Using Deep Learning and Big Data," IJERPH, MDPI, vol. 15(8), pages 1-20, July.
15. Ibrahim Musa & Hyun Woo Park & Lkhagvadorj Munkhdalai & Keun Ho Ryu, 2018. "Global Research on Syndromic Surveillance from 1993 to 2017: Bibliometric Analysis and Visualization," Sustainability, MDPI, vol. 10(10), pages 1-20, September.
16. Logan C Brooks & David C Farrow & Sangwon Hyun & Ryan J Tibshirani & Roni Rosenfeld, 2015. "Flexible Modeling of Epidemics with an Empirical Bayes Framework," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-18, August.
17. Shangfang Dai & Litao Han, 2023. "Influenza surveillance with Baidu index and attention-based long short-term memory model," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-20, January.
18. Daniel Alejandro Gónzalez-Bandala & Juan Carlos Cuevas-Tello & Daniel E. Noyola & Andreu Comas-García & Christian A García-Sepúlveda, 2020. "Computational Forecasting Methodology for Acute Respiratory Infectious Disease Dynamics," IJERPH, MDPI, vol. 17(12), pages 1-20, June.
19. Dan Liu & Songjing Guo & Mingjun Zou & Cong Chen & Fei Deng & Zhong Xie & Sheng Hu & Liang Wu, 2019. "A dengue fever predicting model based on Baidu search index data and climate data in South China," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-16, December.
20. Chris Allen & Ming-Hsiang Tsou & Anoshe Aslam & Anna Nagel & Jean-Mark Gawron, 2016. "Applying GIS and Machine Learning Methods to Twitter Data for Multiscale Surveillance of Influenza," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-10, July.
21. Livio Fenga, 2020. "Filtering and prediction of noisy and unstable signals: The case of Google Trends data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 281-295, March.
22. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
23. Tian-Shyug Lee & I-Fei Chen & Ting-Jen Chang & Chi-Jie Lu, 2020. "Forecasting Weekly Influenza Outpatient Visits Using a Two-Dimensional Hierarchical Decision Tree Scheme," IJERPH, MDPI, vol. 17(13), pages 1-15, July.
24. Kookjin Lee & Jaideep Ray & Cosmin Safta, 2021. "The predictive skill of convolutional neural networks models for disease forecasting," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-26, July.
25. Qingguo Ma & Wuke Zhang, 2015. "Public Mood and Consumption Choices: Evidence from Sales of Sony Cameras on Taobao," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-11, April.
26. Nicolás Gonzálvez‐Gallego & María Concepción Pérez‐Cárceles & Laura Nieto‐Torrejón, 2024. "Do search queries predict violence against women? A forecasting model based on Google Trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1607-1614, August.