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Citing this Article

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Published on 04.10.12 in Vol 14, No 5 (2012): Sep-Oct

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

Works citing "FluBreaks: Early Epidemic Detection from Google Flu Trends"

Fahad Pervaiz, Mansoor Pervaiz, Nabeel Abdur Rehman, Umar Saif

J Med Internet Res 2012 (Oct 04); 14(5):e125 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2102):

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

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  4. Samson SI, Konty K, Lee W, Quisel T, Foschini L, Kerr D, Liska J, Mills H, Hollingsworth R, Greenberg M, Beal AC. Quantifying the Impact of Influenza Among Persons With Type 2 Diabetes Mellitus: A New Approach to Determine Medical and Physical Activity Impact. Journal of Diabetes Science and Technology 2021;15(1):44
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  5. Szmuda T, Ali S, Hetzger TV, Rosvall P, Słoniewski P. Are online searches for the novel coronavirus (COVID-19) related to media or epidemiology? A cross-sectional study. International Journal of Infectious Diseases 2020;97:386
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  6. Zhang Z, Zheng X, Zeng DD, Leischow SJ. Tracking Dabbing Using Search Query Surveillance: A Case Study in the United States. Journal of Medical Internet Research 2016;18(9):e252
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  10. Hanson CL, Cannon B, Burton S, Giraud-Carrier C. An Exploration of Social Circles and Prescription Drug Abuse Through Twitter. Journal of Medical Internet Research 2013;15(9):e189
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  11. Tana JC, Kettunen J, Eirola E, Paakkonen H. Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data. JMIR Mental Health 2018;5(2):e43
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  12. Seo D, Jo M, Sohn CH, Shin S, Lee J, Yu M, Kim WY, Lim KS, Lee S. Cumulative Query Method for Influenza Surveillance Using Search Engine Data. Journal of Medical Internet Research 2014;16(12):e289
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  13. Gesser-Edelsburg A, Shir-Raz Y, Walter N, Mordini E, Dimitriou D, James JJ, Green MS. The Public Sphere in Emerging Infectious Disease Communication: Recipient or Active and Vocal Partner?. Disaster Medicine and Public Health Preparedness 2015;9(4):447
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  14. Mccallum ML, Bury GW. Google search patterns suggest declining interest in the environment. Biodiversity and Conservation 2013;22(6-7):1355
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  16. Barros JM, Duggan J, Rebholz-Schuhmann D. The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review. Journal of Medical Internet Research 2020;22(3):e13680
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  17. Li EY, Tung C, Chang S. The wisdom of crowds in action: Forecasting epidemic diseases with a web-based prediction market system. International Journal of Medical Informatics 2016;92:35
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  19. Zhang Y, Bambrick H, Mengersen K, Tong S, Feng L, Zhang L, Liu G, Xu A, Hu W. Association of sociodemographic factors and internet query data with pertussis infections in Shandong, China. Epidemiology and Infection 2019;147
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  20. Zou S, Veeravalli VV, Li J, Towsley D. Quickest Detection of Dynamic Events in Networks. IEEE Transactions on Information Theory 2020;66(4):2280
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  21. 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
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  22. Mudunuri US, Khouja M, Repetski S, Venkataraman G, Che A, Luke BT, Girard FP, Stephens RM, Aerts J. Knowledge and Theme Discovery across Very Large Biological Data Sets Using Distributed Queries: A Prototype Combining Unstructured and Structured Data. PLoS ONE 2013;8(12):e80503
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  23. Ali A, Qadir J, Rasool RU, Sathiaseelan A, Zwitter A, Crowcroft J. Big data for development: applications and techniques. Big Data Analytics 2016;1(1)
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  24. Liang B, Scammon DL. Incidence of Online Health Information Search: A Useful Proxy for Public Health Risk Perception. Journal of Medical Internet Research 2013;15(6):e114
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  25. Haney NM, Kinsella SD, Morey JM. United States Medical School Graduate Interest in Radiology Residency Programs as Depicted by Online Search Tools. Journal of the American College of Radiology 2014;11(2):193
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  26. Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Chen Y. Assessing Epidemic Diseases and Public Opinion through Popular Search Behavior Using Non-English Language Google Trends (Preprint). JMIR Public Health and Surveillance 2018;
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  27. Schootman M, Toor A, Cavazos-Rehg P, Jeffe DB, McQueen A, Eberth J, Davidson NO. The utility of Google Trends data to examine interest in cancer screening. BMJ Open 2015;5(6):e006678
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  28. Zhang Y, Milinovich G, Xu Z, Bambrick H, Mengersen K, Tong S, Hu W. Monitoring Pertussis Infections Using Internet Search Queries. Scientific Reports 2017;7(1)
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  29. Aslam AA, Tsou M, Spitzberg BH, An L, Gawron JM, Gupta DK, Peddecord KM, Nagel AC, Allen C, Yang J, Lindsay S. The Reliability of Tweets as a Supplementary Method of Seasonal Influenza Surveillance. Journal of Medical Internet Research 2014;16(11):e250
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  30. Rosenkrantz AB, Prabhu V. Public Interest in Imaging-Based Cancer Screening Examinations in the United States: Analysis Using a Web-Based Search Tool. American Journal of Roentgenology 2016;206(1):113
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  31. Klembczyk JJ, Jalalpour M, Levin S, Washington RE, Pines JM, Rothman RE, Dugas AF. Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits. Journal of Medical Internet Research 2016;18(6):e175
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  32. Levin-Rector A, Wilson EL, Fine AD, Greene SK. Refining Historical Limits Method to Improve Disease Cluster Detection, New York City, New York, USA. Emerging Infectious Diseases 2015;21(2):265
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  33. Mahroum N, Bragazzi NL, Brigo F, Waknin R, Sharif K, Mahagna H, Amital H, Watad A. Capturing public interest toward new tools for controlling human immunodeficiency virus (HIV) infection exploiting data from Google Trends. Health Informatics Journal 2019;25(4):1383
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  34. Zheluk A, Quinn C, Hercz D, Gillespie JA. Internet Search Patterns of Human Immunodeficiency Virus and the Digital Divide in the Russian Federation: Infoveillance Study. Journal of Medical Internet Research 2013;15(11):e256
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  35. Herrera JL, Srinivasan R, Brownstein JS, Galvani AP, Meyers LA, Salathé M. Disease Surveillance on Complex Social Networks. PLOS Computational Biology 2016;12(7):e1004928
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  36. Yan S, Chughtai A, Macintyre C. Utility and potential of rapid epidemic intelligence from internet-based sources. International Journal of Infectious Diseases 2017;63:77
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  37. Sugrue R, Carthy E, Kelly ME, Sweeney KJ. Science or popular media: What drives breast cancer online activity?. The Breast Journal 2018;24(2):189
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  38. Stevens KB, Pfeiffer DU. Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems. Spatial and Spatio-temporal Epidemiology 2015;13:15
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  39. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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  40. Abbas M, Morland TB, Hall ES, EL-Manzalawy Y. Associations between Google Search Trends for Symptoms and COVID-19 Confirmed and Death Cases in the United States. International Journal of Environmental Research and Public Health 2021;18(9):4560
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  41. Zhang Y, Bambrick H, Mengersen K, Tong S, Hu W. Using internet-based query and climate data to predict climate-sensitive infectious disease risks: a systematic review of epidemiological evidence. International Journal of Biometeorology 2021;65(12):2203
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  42. Brick JM, Andrews WR, Foster J. A Review of Nonprobability Sampling Using Mobile Apps for Fishing Effort and Catch Surveys. Transactions of the American Fisheries Society 2022;151(1):42
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  43. Chu L, Chen H. Sequential Change-Point Detection for High-Dimensional and Non-Euclidean Data. IEEE Transactions on Signal Processing 2022;70:4498
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  44. Niu Q, Liu J, Zhao Z, Onishi M, Kawaguchi A, Bandara A, Harada K, Aoyama T, Nagai-Tanima M. Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study. BMC Infectious Diseases 2022;22(1)
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  45. Dai S, Han L, Rashid TA. Influenza surveillance with Baidu index and attention-based long short-term memory model. PLOS ONE 2023;18(1):e0280834
    CrossRef
  46. . Global monitoring of public interest in preventive measures against COVID-19 via analysis of Google Trends: an infodemiology and infoveillance study. BMJ Open 2022;12(8):e060715
    CrossRef
  47. Strawbridge JC, Meer EA, Singh P, Rootman DB. Google Searches for Thyroid Eye Disease After Regulatory Approval of Teprotumumab. JAMA Ophthalmology 2022;140(6):639
    CrossRef
  48. Rolnick D, Donti PL, Kaack LH, Kochanski K, Lacoste A, Sankaran K, Ross AS, Milojevic-Dupont N, Jaques N, Waldman-Brown A, Luccioni AS, Maharaj T, Sherwin ED, Mukkavilli SK, Kording KP, Gomes CP, Ng AY, Hassabis D, Platt JC, Creutzig F, Chayes J, Bengio Y. Tackling Climate Change with Machine Learning. ACM Computing Surveys 2023;55(2):1
    CrossRef
  49. Chen H, Chu L. Graph-Based Change-Point Analysis. Annual Review of Statistics and Its Application 2023;10(1):475
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  50. Quinn J, Frias‐Martinez V, Subramanian L. Computational Sustainability and Artificial Intelligence in the Developing World. AI Magazine 2014;35(3):36
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  51. Thakur N, Cui S, Patel KA, Azizi N, Knieling V, Han C, Poon A, Shah R. Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis and Forecasting of Web Behavior. Computation 2023;11(11):234
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.2102):

  1. Nawaz MS, Mustafa RU, Lali MIU. Applying Big Data Analytics in Bioinformatics and Medicine. 2018. chapter 11:272
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  2. Fan S, Garg S, Yeom S. AI 2016: Advances in Artificial Intelligence. 2016. Chapter 63:702
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  3. Goodman KW, Meslin EM. Public Health Informatics and Information Systems. 2014. Chapter 11:191
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  4. Staegemann D, Volk M, Daase C, Pohl M, Turowski K. Proceedings of Sixth International Congress on Information and Communication Technology. 2022. Chapter 25:281
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  5. Burr T, Kaufeld K. Time Series Analysis - New Insights. 2023. Chapter 6
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  6. . Health and Medical Geography in Africa. 2023. Chapter 4:71
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  7. . Effective Use of Social Media in Public Health. 2023. :233
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