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

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

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

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

Authors of this article:

Elad Yom-Tov1 ;   Evgeniy Gabrilovich2

Journals

  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 View
  2. Yom-Tov E. Demographic differences in search engine use with implications for cohort selection. Information Retrieval Journal 2019;22(6):570 View
  3. Hauben M, Reynolds R, Caubel P. Deconstructing the Pharmacovigilance Hype Cycle. Clinical Therapeutics 2018;40(12):1981 View
  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 View
  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) View
  6. White R, 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 View
  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 View
  8. Dong J, Yom-Tov E, Yom-Tov G. The Impact of Delay Announcements on Hospital Network Coordination and Waiting Times. Management Science 2018 View
  9. Gunn L, ter Horst E, Markossian T, Molina G, van Wouwe J. Online interest regarding violent attacks, gun control, and gun purchase: A causal analysis. PLOS ONE 2018;13(11):e0207924 View
  10. Harpaz R, DuMouchel W, Schuemie M, Bodenreider O, Friedman C, Horvitz E, Ripple A, Sorbello A, White R, Winnenburg R, Shah N. Toward multimodal signal detection of adverse drug reactions. Journal of Biomedical Informatics 2017;76:41 View
  11. Tricco A, Zarin W, Lillie E, Jeblee S, Warren R, Khan P, Robson R, Pham B, Hirst G, Straus S. Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review. BMC Medical Informatics and Decision Making 2018;18(1) View
  12. Zeraatkar K, Ahmadi M. Trends of infodemiology studies: a scoping review. Health Information & Libraries Journal 2018;35(2):91 View
  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 View
  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 View
  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) View
  16. Yom-Tov E, Borsa D, Cox I, McKendry R. Detecting Disease Outbreaks in Mass Gatherings Using Internet Data. Journal of Medical Internet Research 2014;16(6):e154 View
  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 View
  18. Hanson C, 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 View
  19. Agarwal V, Zhang L, Zhu J, Fang S, Cheng T, Hong C, Shah N. Impact of Predicting Health Care Utilization Via Web Search Behavior: A Data-Driven Analysis. Journal of Medical Internet Research 2016;18(9):e251 View
  20. Colilla S, Tov E, Zhang L, Kurzinger M, Tcherny-Lessenot S, Penfornis C, Jen S, Gonzalez D, 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 View
  21. Zheluk A, Quinn C, Hercz D, Gillespie J. 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 View
  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 View
  23. Pappa D, Stergioulas L. 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 View
  24. Paul M, Dredze M. Social Monitoring for Public Health. Synthesis Lectures on Information Concepts, Retrieval, and Services 2017;9(5):1 View
  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 View
  26. White R, Hassan A. Content Bias in Online Health Search. ACM Transactions on the Web 2014;8(4):1 View
  27. Vasconcellos-Silva P, Griep R, Souza M. Padrões de acessos a informações sobre proteção antiUV durante os verões brasileiros: haveria um “efeito verão”?. Ciência & Saúde Coletiva 2015;20(8):2533 View
  28. Vaughan Sarrazin M, Cram P, Mazur A, Ward M, Reisinger H. Patient Perspectives of Dabigatran: Analysis of Online Discussion Forums. The Patient - Patient-Centered Outcomes Research 2014;7(1):47 View
  29. Banda J, Evans L, Vanguri R, Tatonetti N, Ryan P, Shah N. A curated and standardized adverse drug event resource to accelerate drug safety research. Scientific Data 2016;3(1) View
  30. Hodos R, Kidd B, Shameer K, Readhead B, Dudley J. In silico methods for drug repurposing and pharmacology. WIREs Systems Biology and Medicine 2016;8(3):186 View
  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 View
  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 View
  33. Yom-Tov E, Borsa D, Hayward A, McKendry R, Cox I. Automatic Identification of Web-Based Risk Markers for Health Events. Journal of Medical Internet Research 2015;17(1):e29 View
  34. Paul M, White R, Horvitz E. Search and Breast Cancer. ACM Transactions on the Web 2016;10(2):1 View
  35. Borchert J, Wang B, Ramzanali M, Stein A, Malaiyandi L, Dineley K. 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 View
  36. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  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 View
  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 View
  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 View
  40. Sadilek A, Hswen Y, Bavadekar S, Shekel T, Brownstein J, Gabrilovich E. Lymelight: forecasting Lyme disease risk using web search data. npj Digital Medicine 2020;3(1) View
  41. Gahr M, Uzelac Z, Zeiss R, Connemann B, 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 View
  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) View
  43. Yom-Tov E, Lebwohl B. Adverse events associated with colonoscopy; an examination of online concerns. BMC Gastroenterology 2019;19(1) View
  44. Yom-Tov E. Screening for Cancer Using a Learning Internet Advertising System. ACM Transactions on Computing for Healthcare 2020;1(2):1 View
  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 View
  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 View
  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 View
  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 View
  49. Polepalli Ramesh B, Belknap S, Li Z, Frid N, West D, 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 View
  50. Yom-Tov E. 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 View
  51. Seo D, Jo M, Sohn C, Shin S, Lee J, Yu M, Kim W, Lim K, Lee S. Cumulative Query Method for Influenza Surveillance Using Search Engine Data. Journal of Medical Internet Research 2014;16(12):e289 View
  52. Dai H, Wang C. Classifying adverse drug reactions from imbalanced twitter data. International Journal of Medical Informatics 2019;129:122 View
  53. Ayers J, Althouse B, Poliak A, Leas E, Nobles A, 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 View
  54. Jacobson N, Yom-Tov E, Lekkas D, Heinz M, Liu L, Barr P. 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 View
  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 View
  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 View
  57. Yom-Tov E, Lampos V, Inns T, Cox I, Edelstein M. Providing early indication of regional anomalies in COVID-19 case counts in England using search engine queries. Scientific Reports 2022;12(1) View
  58. O'Malley P. Drug Recalls and Significance for Safe Clinical Nurse Specialist Prescribing. Clinical Nurse Specialist 2021;35(6):288 View
  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 View
  60. Ahmad F, Abbasi A, Kitchens B, Adjeroh D, Zeng D. Deep Learning for Adverse Event Detection from Web Search. IEEE Transactions on Knowledge and Data Engineering 2020:1 View
  61. Abroms L, 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 View
  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 View
  63. Youngmann B, Yom-Tov E. Intimate Partner Violence as Reflected in Internet Search Data. Social Science Computer Review 2023;41(5):1546 View
  64. Effenberger M, Kronbichler A, Bettac E, Grabherr F, Grander C, Adolph T, 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 View
  65. Keller R, Spanu A, Puhan M, 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 View

Books/Policy Documents

  1. Tropsha A. Applied Chemoinformatics. View
  2. Fernández-Prada C, Douanne N, Minguez-Menendez A, Pena J, Tunes L, Pires D, Monte-Neto R. In Silico Drug Design. View
  3. Gould A. Statistical Methods for Evaluating Safety in Medical Product Development. View
  4. Nawaz M, Mustafa R, Lali M. Applying Big Data Analytics in Bioinformatics and Medicine. View