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Citing this Article

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Published on 18.06.13 in Vol 15, No 6 (2013): June

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

Works citing "Postmarket Drug Surveillance Without Trial Costs: Discovery of Adverse Drug Reactions Through Large-Scale Analysis of Web Search Queries"

Elad Yom-Tov, Evgeniy Gabrilovich

J Med Internet Res 2013 (Jun 18); 15(6):e124 

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2614):

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

  1. Lardon J, Abdellaoui R, Bellet F, Asfari H, Souvignet J, Texier N, Jaulent M, Beyens M, Burgun A, Bousquet C. Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review. Journal of Medical Internet Research 2015;17(7):e171
    CrossRef
  2. . Demographic differences in search engine use with implications for cohort selection. Information Retrieval Journal 2019;22(6):570
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  3. Hauben M, Reynolds R, Caubel P. Deconstructing the Pharmacovigilance Hype Cycle. Clinical Therapeutics 2018;40(12):1981
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  4. Kürzinger M, Schück S, Texier N, Abdellaoui R, Faviez C, Pouget J, Zhang L, Tcherny-Lessenot S, Lin S, Juhaeri J. Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis. Journal of Medical Internet Research 2018;20(11):e10466
    CrossRef
  5. Yom-Tov E, Shembekar J, Barclay S, Muennig P. The effectiveness of public health advertisements to promote health: a randomized-controlled trial on 794,000 participants. npj Digital Medicine 2018;1(1)
    CrossRef
  6. White RW, Wang S, Pant A, Harpaz R, Shukla P, Sun W, DuMouchel W, Horvitz E. Early identification of adverse drug reactions from search log data. Journal of Biomedical Informatics 2016;59:42
    CrossRef
  7. Yom-Tov E, Lev-Ran S. Adverse Reactions Associated With Cannabis Consumption as Evident From Search Engine Queries. JMIR Public Health and Surveillance 2017;3(4):e77
    CrossRef
  8. Dong J, Yom-Tov E, Yom-Tov GB. The Impact of Delay Announcements on Hospital Network Coordination and Waiting Times. Management Science 2018;
    CrossRef
  9. Gunn LH, ter Horst E, Markossian TW, Molina G, van Wouwe JP. Online interest regarding violent attacks, gun control, and gun purchase: A causal analysis. PLOS ONE 2018;13(11):e0207924
    CrossRef
  10. Harpaz R, DuMouchel W, Schuemie M, Bodenreider O, Friedman C, Horvitz E, Ripple A, Sorbello A, White RW, Winnenburg R, Shah NH. Toward multimodal signal detection of adverse drug reactions. Journal of Biomedical Informatics 2017;76:41
    CrossRef
  11. Tricco AC, Zarin W, Lillie E, Jeblee S, Warren R, Khan PA, Robson R, Pham B, Hirst G, Straus SE. Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review. BMC Medical Informatics and Decision Making 2018;18(1)
    CrossRef
  12. Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91
    CrossRef
  13. Lebwohl B, Yom-Tov E. Symptoms Prompting Interest in Celiac Disease and the Gluten-Free Diet: Analysis of Internet Search Term Data. Journal of Medical Internet Research 2019;21(4):e13082
    CrossRef
  14. Li Y, Jimeno Yepes A, Xiao C. Combining Social Media and FDA Adverse Event Reporting System to Detect Adverse Drug Reactions. Drug Safety 2020;43(9):893
    CrossRef
  15. Sampathkumar H, Chen X, Luo B. Mining Adverse Drug Reactions from online healthcare forums using Hidden Markov Model. BMC Medical Informatics and Decision Making 2014;14(1)
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  16. Yom-Tov E, Borsa D, Cox IJ, McKendry RA. Detecting Disease Outbreaks in Mass Gatherings Using Internet Data. Journal of Medical Internet Research 2014;16(6):e154
    CrossRef
  17. Giat E, Yom-Tov E. Evidence From Web-Based Dietary Search Patterns to the Role of B12 Deficiency in Non-Specific Chronic Pain: A Large-Scale Observational Study. Journal of Medical Internet Research 2018;20(1):e4
    CrossRef
  18. 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
    CrossRef
  19. 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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  20. Colilla S, Tov EY, Zhang L, Kurzinger M, Tcherny-Lessenot S, Penfornis C, Jen S, Gonzalez DS, Caubel P, Welsh S, Juhaeri J. Validation of New Signal Detection Methods for Web Query Log Data Compared to Signal Detection Algorithms Used With FAERS. Drug Safety 2017;40(5):399
    CrossRef
  21. 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
    CrossRef
  22. Yom-Tov E, Brunstein-Klomek A, Hadas A, Tamir O, Fennig S. Differences in physical status, mental state and online behavior of people in pro-anorexia web communities. Eating Behaviors 2016;22:109
    CrossRef
  23. Pappa D, Stergioulas LK. Harnessing social media data for pharmacovigilance: a review of current state of the art, challenges and future directions. International Journal of Data Science and Analytics 2019;8(2):113
    CrossRef
  24. Paul MJ, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1
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  25. Nitzburg G, Weber I, Yom-Tov E. Internet Searches for Medical Symptoms Before Seeking Information on 12-Step Addiction Treatment Programs: A Web-Search Log Analysis. Journal of Medical Internet Research 2019;21(5):e10946
    CrossRef
  26. White RW, Hassan A. Content Bias in Online Health Search. ACM Transactions on the Web 2014;8(4):1
    CrossRef
  27. Vasconcellos-Silva PR, Griep RH, Souza MCD. Padrões de acessos a informações sobre proteção antiUV durante os verões brasileiros: haveria um “efeito verão”?. Ciência & Saúde Coletiva 2015;20(8):2533
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  28. Vaughan Sarrazin MS, Cram P, Mazur A, Ward M, Reisinger HS. Patient Perspectives of Dabigatran: Analysis of Online Discussion Forums. The Patient - Patient-Centered Outcomes Research 2014;7(1):47
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  29. Banda JM, Evans L, Vanguri RS, Tatonetti NP, Ryan PB, Shah NH. A curated and standardized adverse drug event resource to accelerate drug safety research. Scientific Data 2016;3(1)
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  30. Hodos RA, Kidd BA, Shameer K, Readhead BP, Dudley JT. In silico methods for drug repurposing and pharmacology. WIREs Systems Biology and Medicine 2016;8(3):186
    CrossRef
  31. Hochberg I, Daoud D, Shehadeh N, Yom-Tov E. Can internet search engine queries be used to diagnose diabetes? Analysis of archival search data. Acta Diabetologica 2019;56(10):1149
    CrossRef
  32. Hochberg I, Allon R, Yom-Tov E. Assessment of the Frequency of Online Searches for Symptoms Before Diagnosis: Analysis of Archival Data. Journal of Medical Internet Research 2020;22(3):e15065
    CrossRef
  33. Yom-Tov E, Borsa D, Hayward AC, McKendry RA, Cox IJ. Automatic Identification of Web-Based Risk Markers for Health Events. Journal of Medical Internet Research 2015;17(1):e29
    CrossRef
  34. Paul MJ, White RW, Horvitz E. Search and Breast Cancer. ACM Transactions on the Web 2016;10(2):1
    CrossRef
  35. Borchert JS, Wang B, Ramzanali M, Stein AB, Malaiyandi LM, Dineley KE. Adverse Events Due to Insomnia Drugs Reported in a Regulatory Database and Online Patient Reviews: Comparative Study. Journal of Medical Internet Research 2019;21(11):e13371
    CrossRef
  36. . Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206
    CrossRef
  37. Sharma V, Holmes J, Sarkar I. Identifying Complementary and Alternative Medicine Usage Information from Internet Resources. Methods of Information in Medicine 2016;55(04):322
    CrossRef
  38. Karimi S, Wang C, Metke-Jimenez A, Gaire R, Paris C. Text and Data Mining Techniques in Adverse Drug Reaction Detection. ACM Computing Surveys 2015;47(4):1
    CrossRef
  39. Menachemi N, Rahurkar S, Rahurkar M. Using Web-Based Search Data to Study the Public’s Reactions to Societal Events: The Case of the Sandy Hook Shooting. JMIR Public Health and Surveillance 2017;3(1):e12
    CrossRef
  40. Sadilek A, Hswen Y, Bavadekar S, Shekel T, Brownstein JS, Gabrilovich E. Lymelight: forecasting Lyme disease risk using web search data. npj Digital Medicine 2020;3(1)
    CrossRef
  41. Gahr M, Uzelac Z, Zeiss R, Connemann BJ, Lang D, Schönfeldt-Lecuona C. Linking Annual Prescription Volume of Antidepressants to Corresponding Web Search Query Data. Journal of Clinical Psychopharmacology 2015;35(6):681
    CrossRef
  42. Oren E, Frere J, Yom-Tov E, Yom-Tov E. Respiratory syncytial virus tracking using internet search engine data. BMC Public Health 2018;18(1)
    CrossRef
  43. Yom-Tov E, Lebwohl B. Adverse events associated with colonoscopy; an examination of online concerns. BMC Gastroenterology 2019;19(1)
    CrossRef
  44. . Screening for Cancer Using a Learning Internet Advertising System. ACM Transactions on Computing for Healthcare 2020;1(2):1
    CrossRef
  45. Tutubalina E, Nikolenko S. Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews. Journal of Healthcare Engineering 2017;2017:1
    CrossRef
  46. Soldaini L, Yates A, Yom-Tov E, Frieder O, Goharian N. Enhancing web search in the medical domain via query clarification. Information Retrieval Journal 2016;19(1-2):149
    CrossRef
  47. Trifirò G, Sultana J, Bate A. From Big Data to Smart Data for Pharmacovigilance: The Role of Healthcare Databases and Other Emerging Sources. Drug Safety 2018;41(2):143
    CrossRef
  48. Abbasi A, Li J, Abbasi S, Adjeroh D, Abate M, Zheng W. Don't Mention It? Analyzing User-Generated Content Signals for Early Adverse Drug Event Warnings. SSRN Electronic Journal 2015;
    CrossRef
  49. Polepalli Ramesh B, Belknap SM, Li Z, Frid N, West DP, Yu H. Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration’s Adverse Event Reporting System Narratives. JMIR Medical Informatics 2014;2(1):e10
    CrossRef
  50. . Predicting Drug Recalls from Internet Search Engine Queries These findings suggest that aggregated Internet search engine data can be used to facilitate in early warning of faulty batches of medicines.. IEEE Journal of Translational Engineering in Health and Medicine 2017;:1
    CrossRef
  51. 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
    CrossRef
  52. Dai H, Wang C. Classifying adverse drug reactions from imbalanced twitter data. International Journal of Medical Informatics 2019;129:122
    CrossRef
  53. Ayers JW, Althouse BM, Poliak A, Leas EC, Nobles AL, Dredze M, Smith D. Quantifying Public Interest in Police Reforms by Mining Internet Search Data Following George Floyd’s Death. Journal of Medical Internet Research 2020;22(10):e22574
    CrossRef
  54. Jacobson NC, Yom-Tov E, Lekkas D, Heinz M, Liu L, Barr PJ. Impact of online mental health screening tools on help-seeking, care receipt, and suicidal ideation and suicidal intent: Evidence from internet search behavior in a large U.S. cohort. Journal of Psychiatric Research 2022;145:276
    CrossRef
  55. Hswen Y, Yom-Tov E. Analysis of a Vaping-Associated Lung Injury Outbreak through Participatory Surveillance and Archival Internet Data. International Journal of Environmental Research and Public Health 2021;18(15):8203
    CrossRef
  56. Chen R, Zhang Y, Dou Z, Chen F, Xie K, Wang S. Data Sharing and Privacy in Pharmaceutical Studies. Current Pharmaceutical Design 2021;27(7):911
    CrossRef
  57. Yom-Tov E, Lampos V, Inns T, Cox IJ, Edelstein M. Providing early indication of regional anomalies in COVID-19 case counts in England using search engine queries. Scientific Reports 2022;12(1)
    CrossRef
  58. . Drug Recalls and Significance for Safe Clinical Nurse Specialist Prescribing. Clinical Nurse Specialist 2021;35(6):288
    CrossRef
  59. Kamba M, Manabe M, Wakamiya S, Yada S, Aramaki E, Odani S, Miyashiro I. Medical Needs Extraction for Breast Cancer Patients from Question and Answer Services: Natural Language Processing-Based Approach. JMIR Cancer 2021;7(4):e32005
    CrossRef
  60. Ahmad F, Abbasi A, Kitchens B, Adjeroh DA, Zeng D. Deep Learning for Adverse Event Detection from Web Search. IEEE Transactions on Knowledge and Data Engineering 2020;:1
    CrossRef
  61. Abroms LC, Yom-Tov E. The Role of Information Boxes in Search Engine Results for Symptom Searches: Analysis of Archival Data. JMIR Infodemiology 2022;2(2):e37286
    CrossRef
  62. Déguilhem A, Malaab J, Talmatkadi M, Renner S, Foulquié P, Fagherazzi G, Loussikian P, Marty T, Mebarki A, Texier N, Schuck S. Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media. JMIR Infodemiology 2022;2(2):e39849
    CrossRef
  63. Youngmann B, Yom-Tov E. Intimate Partner Violence as Reflected in Internet Search Data. Social Science Computer Review 2023;41(5):1546
    CrossRef
  64. Effenberger M, Kronbichler A, Bettac E, Grabherr F, Grander C, Adolph TE, Mayer G, Zoller H, Perco P, Tilg H. Using Infodemiology Metrics to Assess Public Interest in Liver Transplantation: Google Trends Analysis. Journal of Medical Internet Research 2021;23(8):e21656
    CrossRef
  65. Keller R, Spanu A, Puhan MA, Flahault A, Lovis C, Mütsch M, Beau-Lejdstrom R. Social media and internet search data to inform drug utilization: A systematic scoping review. Frontiers in Digital Health 2023;5
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.2614):

  1. . Applied Chemoinformatics. 2018. :395
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  2. Fernández-Prada C, Douanne N, Minguez-Menendez A, Pena J, Tunes LG, Pires DE, Monte-Neto RL. In Silico Drug Design. 2019. :119
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  3. . Statistical Methods for Evaluating Safety in Medical Product Development. 2014. :345
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  4. Nawaz MS, Mustafa RU, Lali MIU. Applying Big Data Analytics in Bioinformatics and Medicine. 2018. chapter 11:272
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