Published on in Vol 19, No 9 (2017): September

Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data

Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data

Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data

Authors of this article:

Ireneus Kagashe1 Author Orcid Image ;   Zhijun Yan1, 2 Author Orcid Image ;   Imran Suheryani3 Author Orcid Image

Journals

  1. Wang J, Deng H, Liu B, Hu A, Liang J, Fan L, Zheng X, Wang T, Lei J. Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed. Journal of Medical Internet Research 2020;22(1):e16816 View
  2. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  3. Alessa A, Faezipour M. Flu Outbreak Prediction Using Twitter Posts Classification and Linear Regression With Historical Centers for Disease Control and Prevention Reports: Prediction Framework Study. JMIR Public Health and Surveillance 2019;5(2):e12383 View
  4. Puri N, Coomes E, Haghbayan H, Gunaratne K. Social media and vaccine hesitancy: new updates for the era of COVID-19 and globalized infectious diseases. Human Vaccines & Immunotherapeutics 2020;16(11):2586 View
  5. Mavragani A, Sampri A, Sypsa K, Tsagarakis K. 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 View
  6. Nimesh S. The Role of Pharmacist in the Health Care System: Current Scenario in India. Borneo Journal of Pharmacy 2020;3(2):84 View
  7. Gao J, Zhang Y, Zhou T. Computational socioeconomics. Physics Reports 2019;817:1 View
  8. Mahroum N, Adawi M, Sharif K, Waknin R, Mahagna H, Bisharat B, Mahamid M, Abu-Much A, Amital H, Luigi Bragazzi N, Watad A, Manogaran G. Public reaction to Chikungunya outbreaks in Italy—Insights from an extensive novel data streams-based structural equation modeling analysis. PLOS ONE 2018;13(5):e0197337 View
  9. Weissenbacher D, Sarker A, Klein A, O’Connor K, Magge A, Gonzalez-Hernandez G. Deep neural networks ensemble for detecting medication mentions in tweets. Journal of the American Medical Informatics Association 2019;26(12):1618 View
  10. Logghe H, Selby L, Boeck M, Stamp N, Chuen J, Jones C. The academic tweet: Twitter as a tool to advance academic surgery. Journal of Surgical Research 2018;226:viii View
  11. Huang M, ElTayeby O, Zolnoori M, Yao L. Public Opinions Toward Diseases: Infodemiological Study on News Media Data. Journal of Medical Internet Research 2018;20(5):e10047 View
  12. Liang F, Guan P, Wu W, Huang D. Forecasting influenza epidemics by integrating internet search queries and traditional surveillance data with the support vector machine regression model in Liaoning, from 2011 to 2015. PeerJ 2018;6:e5134 View
  13. Amith M, Cohen T, Cunningham R, Savas L, Smith N, Cuccaro P, Gabay E, Boom J, Schvaneveldt R, Tao C. Mining HPV Vaccine Knowledge Structures of Young Adults From Reddit Using Distributional Semantics and Pathfinder Networks. Cancer Control 2020;27(1) View
  14. Junwei K, Yang H, Junjiang L, Zhijun Y. Dynamic prediction of cardiovascular disease using improved LSTM. International Journal of Crowd Science 2019;3(1):14 View
  15. Du J, Cunningham R, Xiang Y, Li F, Jia Y, Boom J, Myneni S, Bian J, Luo C, Chen Y, Tao C. Leveraging deep learning to understand health beliefs about the Human Papillomavirus Vaccine from social media. npj Digital Medicine 2019;2(1) View
  16. Zhu B, Zheng X, Liu H, Li J, Wang P. Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics. Chaos, Solitons & Fractals 2020;140:110123 View
  17. Yang H, Gao H. Toward Sustainable Virtualized Healthcare: Extracting Medical Entities from Chinese Online Health Consultations Using Deep Neural Networks. Sustainability 2018;10(9):3292 View
  18. Cai M, Shah N, Li J, Chen W, Cuomo R, Obradovich N, Mackey T, Lavorgna L. Identification and characterization of tweets related to the 2015 Indiana HIV outbreak: A retrospective infoveillance study. PLOS ONE 2020;15(8):e0235150 View
  19. Hanna A, Hanna L. Topic Analysis of UK Fitness to Practise Cases: What Lessons Can Be Learnt?. Pharmacy 2019;7(3):130 View
  20. Barros J, 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 View
  21. Edo-Osagie O, De La Iglesia B, Lake I, Edeghere O. A scoping review of the use of Twitter for public health research. Computers in Biology and Medicine 2020;122:103770 View
  22. Mutanga M, Abayomi A. Tweeting on COVID-19 pandemic in South Africa: LDA-based topic modelling approach. African Journal of Science, Technology, Innovation and Development 2022;14(1):163 View
  23. Gabarron E, Rivera-Romero O, Miron-Shatz T, Grainger R, Denecke K. Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review. Yearbook of Medical Informatics 2021;30(01):200 View
  24. Huang N, Yan Z, Yin H. Effects of Online-Offline Service Integration on e-Healthcare Providers: A Quasi-Natural Experiment. SSRN Electronic Journal 2021 View
  25. Huang N, Yan Z, Yin H. Effects of Online–Offline Service Integration on e‐Healthcare Providers: A Quasi‐Natural Experiment. Production and Operations Management 2021;30(8):2359 View
  26. Li L, Novillo-Ortiz D, Azzopardi-Muscat N, Kostkova P. Digital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews. Frontiers in Public Health 2021;9 View
  27. Palomares I, Martínez-Cámara E, Montes R, García-Moral P, Chiachio M, Chiachio J, Alonso S, Melero F, Molina D, Fernández B, Moral C, Marchena R, de Vargas J, Herrera F. A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects. Applied Intelligence 2021;51(9):6497 View
  28. Wu J, Sivaraman V, Kumar D, Banda J, Sontag D. Pulse of the pandemic: Iterative topic filtering for clinical information extraction from social media. Journal of Biomedical Informatics 2021;120:103844 View
  29. Wahid J, Shi L, Gao Y, Yang B, Tao Y, Wei L, Hussain S. Identifying and Characterizing the Propagation Scale of COVID-19 Situational Information on Twitter: A Hybrid Text Analytic Approach. Applied Sciences 2021;11(14):6526 View
  30. Kostkova P, Saigí-Rubió F, Eguia H, Borbolla D, Verschuuren M, Hamilton C, Azzopardi-Muscat N, Novillo-Ortiz D. Data and Digital Solutions to Support Surveillance Strategies in the Context of the COVID-19 Pandemic. Frontiers in Digital Health 2021;3 View
  31. Hagg L, Merkouris S, O’Dea G, Francis L, Greenwood C, Fuller-Tyszkiewicz M, Westrupp E, Macdonald J, Youssef G. Examining Analytic Practices in Latent Dirichlet Allocation Within Psychological Science: Scoping Review. Journal of Medical Internet Research 2022;24(11):e33166 View
  32. Alhazmi H. Arabic Twitter Conversation Dataset about the COVID-19 Vaccine. Data 2022;7(11):152 View
  33. Azizi F, Hajiabadi H, Vahdat-Nejad H, Khosravi M. Detecting and analyzing topics of massive COVID-19 related tweets for various countries. Computers and Electrical Engineering 2023;106:108561 View
  34. Pu X, Jiang Q, Fan B. Chinese public opinion on Japan's nuclear wastewater discharge: A case study of Weibo comments based on a thematic model. Ocean & Coastal Management 2022;225:106188 View
  35. Pilipiec P, Samsten I, Bota A, Rocha L. Surveillance of communicable diseases using social media: A systematic review. PLOS ONE 2023;18(2):e0282101 View
  36. Noble P, Appleton C, Radford A, Nenadic G, Dórea F. Using topic modelling for unsupervised annotation of electronic health records to identify an outbreak of disease in UK dogs. PLOS ONE 2021;16(12):e0260402 View
  37. Alves V, Korn D, Pervitsky V, Thieme A, Capuzzi S, Baker N, Chirkova R, Ekins S, Muratov E, Hickey A, Tropsha A. Knowledge-based approaches to drug discovery for rare diseases. Drug Discovery Today 2022;27(2):490 View
  38. Kostarella I, Kotsakis R. The Effects of the COVID-19 “Infodemic” on Journalistic Content and News Feed in Online and Offline Communication Spaces. Journalism and Media 2022;3(3):471 View
  39. Sarker A, Gonzalez-Hernandez G. An unsupervised and customizable misspelling generator for mining noisy health-related text sources. Journal of Biomedical Informatics 2018;88:98 View
  40. Fu J, Li C, Zhou C, Li W, Lai J, Deng S, Zhang Y, Guo Z, Wu Y. Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review. Journal of Medical Internet Research 2023;25:e43349 View
  41. Butt M, Malik A, Qamar N, Yar S, Malik A, Rauf U. A Survey on COVID-19 Data Analysis Using AI, IoT, and Social Media. Sensors 2023;23(12):5543 View
  42. Huang L, Eiden A, He L, Annan A, Wang S, Wang J, Manion F, Wang X, Du J, Yao L. Natural Language Processing–Powered Real-Time Monitoring Solution for Vaccine Sentiments and Hesitancy on Social Media: System Development and Validation. JMIR Medical Informatics 2024;12:e57164 View
  43. Al-Haider M, Qamar A, Alkahtani H, Ahmad H. Classification of Obsessive-Compulsive Disorder Symptoms in Arabic Tweets Using Machine Learning and Word Embedding Techniques. Journal of Advances in Information Technology 2024;15(7):798 View

Books/Policy Documents

  1. Alves V, Capuzzi S, Baker N, Muratov E, Trospsha A, Hickey A. Approaching Complex Diseases. View
  2. Wang K, He C, Wang L, Wu J. Knowledge and Systems Sciences. View