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Citing this Article

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Published on 14.04.20 in Vol 6, No 2 (2020): Apr-Jun

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

Works citing "Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study"

According to Crossref, the following articles are citing this article (DOI 10.2196/18828):

(note that this is only a small subset of citations)

  1. Ahmad A, Garhwal S, Ray SK, Kumar G, Malebary SJ, Barukab OM. The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges. Archives of Computational Methods in Engineering 2020;
    CrossRef
  2. Swapnarekha H, Behera HS, Nayak J, Naik B. Role of intelligent computing in COVID-19 prognosis: A state-of-the-art review. Chaos, Solitons & Fractals 2020;138:109947
    CrossRef
  3. Ramchandani A, Fan C, Mostafavi A. DeepCOVIDNet: An Interpretable Deep Learning Model for Predictive Surveillance of COVID-19 Using Heterogeneous Features and Their Interactions. IEEE Access 2020;8:159915
    CrossRef
  4. Alencar DDC, Passos JA, Carvalho ARBD, Ibiapina ARDS, Carvalho DBF, Vasconcellos-Silva PR. Busca de informações sobre o novo coronavírus no Brasil: uma análise da tendência considerando as buscas online. Acta Paulista de Enfermagem 2020;33
    CrossRef
  5. Cousins HC, Cousins CC, Harris A, Pasquale LR. Regional Infoveillance of COVID-19 Case Rates: Analysis of Search-Engine Query Patterns. Journal of Medical Internet Research 2020;22(7):e19483
    CrossRef
  6. Ortiz-Martínez Y, Garcia-Robledo JE, Vásquez-Castañeda DL, Bonilla-Aldana DK, Rodriguez-Morales AJ. Can Google® trends predict COVID-19 incidence and help preparedness? The situation in Colombia. Travel Medicine and Infectious Disease 2020;:101703
    CrossRef
  7. Zhang T. Data mining can play a critical role in COVID-19 linked mental health studies. Asian Journal of Psychiatry 2020;54:102399
    CrossRef
  8. Dalanon J, Matsuka Y. Forecasting Interest in Health Professions Education Based on Relative Search Volume Trends From the Philippines. Health Professions Education 2020;6(3):368
    CrossRef
  9. Fagherazzi G, Goetzinger C, Rashid MA, Aguayo GA, Huiart L. Digital Health Strategies to Fight COVID-19 Worldwide: Challenges, Recommendations, and a Call for Papers. Journal of Medical Internet Research 2020;22(6):e19284
    CrossRef
  10. Sousa-Pinto B, Anto A, Czarlewski W, Anto JM, Fonseca JA, Bousquet J. Assessment of the Impact of Media Coverage on COVID-19–Related Google Trends Data: Infodemiology Study. Journal of Medical Internet Research 2020;22(8):e19611
    CrossRef
  11. Yuan X, Xu J, Hussain S, Wang H, Gao N, Zhang L. Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model. Exploratory Research and Hypothesis in Medicine 2020;000(000):1
    CrossRef
  12. Walker MD, Sulyok M. Online behavioural patterns for Coronavirus disease 2019 (COVID-19) in the United Kingdom. Epidemiology and Infection 2020;148
    CrossRef
  13. Sufian A, Ghosh A, Sadiq AS, Smarandache F. A Survey on Deep Transfer Learning to Edge Computing for Mitigating the COVID-19 Pandemic. Journal of Systems Architecture 2020;108:101830
    CrossRef
  14. Lin Y, Liu C, Chiu Y. Google searches for the keywords of “wash hands” predict the speed of national spread of COVID-19 outbreak among 21 countries. Brain, Behavior, and Immunity 2020;87:30
    CrossRef
  15. Ciaffi J, Meliconi R, Landini MP, Ursini F. Google trends and COVID-19 in Italy: could we brace for impact?. Internal and Emergency Medicine 2020;
    CrossRef
  16. Eltoukhy AEE, Shaban IA, Chan FTS, Abdel-Aal MAM. Data Analytics for Predicting COVID-19 Cases in Top Affected Countries: Observations and Recommendations. International Journal of Environmental Research and Public Health 2020;17(19):7080
    CrossRef
  17. Naseem M, Akhund R, Arshad H, Ibrahim MT. Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review. Journal of Primary Care & Community Health 2020;11:215013272096363
    CrossRef
  18. Tayarani-N. M. Applications of Artificial Intelligence in Battling Against Covid-19: A Literature Review. Chaos, Solitons & Fractals 2020;:110338
    CrossRef