Published on 19.11.15 in Vol 17, No 11 (2015): November
Works citing "Forecasting the Incidence of Dementia and Dementia-Related Outpatient Visits With Google Trends: Evidence From Taiwan"
According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.4516):
(note that this is only a small subset of citations)
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Ransohoff J, Sarin K. Referred by Google: mining Google Trends data to identify patterns in and correlates to searches for dermatological concerns and providers. British Journal of Dermatology 2018;178(3):794
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Mavragani A, Ochoa G, Tsagarakis KP. Assessing the Methods, Tools, and Statistical Approaches in Google Trends Research: Systematic Review. Journal of Medical Internet Research 2018;20(11):e270
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Mavragani A, Sypsa K, Sampri A, Tsagarakis K. Quantifying the UK Online Interest in Substances of the EU Watchlist for Water Monitoring: Diclofenac, Estradiol, and the Macrolide Antibiotics. Water 2016;8(11):542
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Berlinberg EJ, Deiner MS, Porco TC, Acharya NR. Monitoring Interest in Herpes Zoster Vaccination: Analysis of Google Search Data. JMIR Public Health and Surveillance 2018;4(2):e10180
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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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. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
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Ssendikaddiwa J, Lavergne R. Access to Primary Care and Internet Searches for Walk-In Clinics and Emergency Departments in Canada: Observational Study Using Google Trends and Population Health Survey Data. JMIR Public Health and Surveillance 2019;5(4):e13130
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Gafson A, Craner MJ, Matthews PM. Personalised medicine for multiple sclerosis care. Multiple Sclerosis Journal 2017;23(3):362
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Mavragani A, Sampri A, Tsagarakis KP. Quantifying the Online Behavior Towards Organic Micropollutants of the EU Watchlist: The Cases of Diclofenac & the Macrolide Antibiotics. Procedia Engineering 2016;162:576
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Luo L, Liao C, Zhang F, Zhang W, Li C, Qiu Z, Huang D. Applicability of internet search index for asthma admission forecast using machine learning. The International Journal of Health Planning and Management 2018;33(3):723
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Agarwal V, Zhang L, Zhu J, Fang S, Cheng T, Hong C, Shah NH. Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis. Journal of Medical Internet Research 2016;18(9):e251
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Yang P, Shih M, Liu Y, Hsu Y, Chang H, Lin M, Chen T, Chou L, Hwang S. Web Search Trends of Implementing the Patient Autonomy Act in Taiwan. Healthcare 2020;8(3):353
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Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91
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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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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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Mavragani A, Sampri A, Sypsa K, Tsagarakis KP. Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era. JMIR Public Health and Surveillance 2018;4(1):e24
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Memon SA, Razak S, Weber I. Lifestyle Disease Surveillance Using Population Search Behavior: Feasibility Study. Journal of Medical Internet Research 2020;22(1):e13347
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Chang Y, Chiang W, Wang W, Lin C, Hung L, Tsai Y, Suen J, Chen Y. Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan. BMJ Open 2020;10(7):e034156
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Jaakkimainen RL, Bronskill SE, Tierney MC, Herrmann N, Green D, Young J, Ivers N, Butt D, Widdifield J, Tu K. Identification of Physician-Diagnosed Alzheimer’s Disease and Related Dementias in Population-Based Administrative Data: A Validation Study Using Family Physicians’ Electronic Medical Records. Journal of Alzheimer's Disease 2016;54(1):337
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Zhang Q, Chai Y, Li X, Young SD, Zhou J. Using internet search data to predict new HIV diagnoses in China: a modelling study. BMJ Open 2018;8(10):e018335
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Mavragani A, Ochoa G. Forecasting AIDS prevalence in the United States using online search traffic data. Journal of Big Data 2018;5(1)
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Ling R, Lee J. Disease Monitoring and Health Campaign Evaluation Using Google Search Activities for HIV and AIDS, Stroke, Colorectal Cancer, and Marijuana Use in Canada: A Retrospective Observational Study. JMIR Public Health and Surveillance 2016;2(2):e156
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Ienca M, Vayena E, Blasimme A. Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy. Frontiers in Medicine 2018;5
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Mavragani A, Ochoa G. Infoveillance of infectious diseases in USA: STDs, tuberculosis, and hepatitis. Journal of Big Data 2018;5(1)
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Mavragani A, Tsagarakis KP. Predicting referendum results in the Big Data Era. Journal of Big Data 2019;6(1)
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Kurian SJ, Bhatti AUR, Alvi MA, Ting HH, Storlie C, Wilson PM, Shah ND, Liu H, Bydon M. Correlations Between COVID-19 Cases and Google Trends Data in the United States: A State-by-State Analysis. Mayo Clinic Proceedings 2020;95(11):2370
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Shehzad A, Rockwood K, Stanley J, Dunn T, Howlett SE. Use of Patient-Reported Symptoms from an Online Symptom Tracking Tool for Dementia Severity Staging: Development and Validation of a Machine Learning Approach. Journal of Medical Internet Research 2020;22(11):e20840
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Martini M, Bragazzi NL. Googling for Neurological Disorders: From Seeking Health-Related Information to Patient Empowerment, Advocacy, and Open, Public Self-Disclosure in the Neurology 2.0 Era. Journal of Medical Internet Research 2021;23(3):e13999
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Olukanmi SO, Nelwamondo FV, Nwulu NI. 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
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Piamonte BLC, Anlacan VMM, Jamora RDG, Espiritu AI. Googling Alzheimer Disease: An Infodemiological and Ecological Study. Dementia and Geriatric Cognitive Disorders Extra 2021;11(3):333
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Mao Y, Wang P, Wang X, Ye D. Global Public Interest and Seasonal Variations in Alzheimer's Disease: Evidence From Google Trends. Frontiers in Medicine 2021;8
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Okunoye B, Ning S, Jemielniak D. Searching for HIV and AIDS Health Information in South Africa, 2004-2019: Analysis of Google and Wikipedia Search Trends. JMIR Formative Research 2022;6(3):e29819
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Gkotsis G, Mueller C, Dobson R, Hubbard T, Dutta R. Mining Social Media Data to Study the Consequences of Dementia Diagnosis on Caregivers and Relatives. Dementia and Geriatric Cognitive Disorders 2020;49(3):295
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Wang D, Guerra A, Wittke F, Lang JC, Bakker K, Lee AW, Finelli L, Chen Y. Real-Time Monitoring of Infectious Disease Outbreaks with a Combination of Google Trends Search Results and the Moving Epidemic Method: A Respiratory Syncytial Virus Case Study. Tropical Medicine and Infectious Disease 2023;8(2):75
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Di Spirito F, Bramanti A, Cannatà D, Coppola N, Di Palo MP, Savarese G, Amato M. Oral and Dental Needs and Teledentistry Applications in the Elderly: Real-Time Surveillance Using Google Trends. Applied Sciences 2023;13(9):5416
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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
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According to Crossref, the following books are citing this article (DOI 10.2196/jmir.4516):