Published on in Vol 5 , No 3 (2017) :Jul-Sept

What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer

What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer

What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer

Journals

  1. Foufi V, Timakum T, Gaudet-Blavignac C, Lovis C, Song M. Mining of Textual Health Information from Reddit: Analysis of Chronic Diseases With Extracted Entities and Their Relations. Journal of Medical Internet Research 2019;21(6):e12876 View
  2. Abdellaoui R, Foulquié P, Texier N, Faviez C, Burgun A, Schück S. Detection of Cases of Noncompliance to Drug Treatment in Patient Forum Posts: Topic Model Approach. Journal of Medical Internet Research 2018;20(3):e85 View
  3. Shah A, Yan X, Tariq S, Khan S. Listening to the patient voice: using a sentic computing model to evaluate physicians’ healthcare service quality for strategic planning in hospitals. Quality & Quantity 2021;55(1):173 View
  4. Badenes-Olmedo C, Redondo-García J, Corcho O, Kauppinen T, Garijo D, Villanueva N, Garijo D, Villanueva-Rosales N, Kauppinen T. Large-scale semantic exploration of scientific literature using topic-based hashing algorithms. Semantic Web 2020;11(5):735 View
  5. Hanna A, Hanna L. Topic Analysis of UK Fitness to Practise Cases: What Lessons Can Be Learnt?. Pharmacy 2019;7(3):130 View
  6. Tapi Nzali M, Aze J, Bringay S, Lavergne C, Mollevi C, Optiz T. Reconciliation of patient/doctor vocabulary in a structured resource. Health Informatics Journal 2019;25(4):1219 View
  7. Cotté F, Voillot P, Bennett B, Falissard B, Tzourio C, Foulquié P, Gaudin A, Lemasson H, Grumberg V, McDonald L, Faviez C, Schück S. Exploring the Health-Related Quality of Life of Patients Treated With Immune Checkpoint Inhibitors: Social Media Study. Journal of Medical Internet Research 2020;22(9):e19694 View
  8. Nasralah T, El-Gayar O, Wang Y. Social Media Text Mining Framework for Drug Abuse: Development and Validation Study With an Opioid Crisis Case Analysis. Journal of Medical Internet Research 2020;22(8):e18350 View
  9. Tran B, Latkin C, Sharafeldin N, Nguyen K, Vu G, Tam W, Cheung N, Nguyen H, Ho C, Ho R. Characterizing Artificial Intelligence Applications in Cancer Research: A Latent Dirichlet Allocation Analysis. JMIR Medical Informatics 2019;7(4):e14401 View
  10. Chen X, Faviez C, Schuck S, Lillo-Le-Louët A, Texier N, Dahamna B, Huot C, Foulquié P, Pereira S, Leroux V, Karapetiantz P, Guenegou-Arnoux A, Katsahian S, Bousquet C, Burgun A. Mining Patients' Narratives in Social Media for Pharmacovigilance: Adverse Effects and Misuse of Methylphenidate. Frontiers in Pharmacology 2018;9 View
  11. Zolnoori M, Balls-Berry J, Brockman T, Patten C, Huang M, Yao L. A Systematic Framework for Analyzing Patient-Generated Narrative Data: Protocol for a Content Analysis. JMIR Research Protocols 2019;8(8):13914 View
  12. Ure C, Cooper-Ryan A, Condie J, Galpin A. Exploring Strategies for Using Social Media to Self-Manage Health Care When Living With and Beyond Breast Cancer: In-Depth Qualitative Study. Journal of Medical Internet Research 2020;22(5):e16902 View
  13. Dumas A, Lapointe A, Desroches S. Users, Uses, and Effects of Social Media in Dietetic Practice: Scoping Review of the Quantitative and Qualitative Evidence. Journal of Medical Internet Research 2018;20(2):e55 View
  14. van Eenbergen M, van de Poll-Franse L, Krahmer E, Verberne S, Mols F. Analysis of Content Shared in Online Cancer Communities: Systematic Review. JMIR Cancer 2018;4(1):e6 View
  15. Lee Y, Kamen C, Margolies L, Boehmer U. Online health community experiences of sexual minority women with cancer. Journal of the American Medical Informatics Association 2019;26(8-9):759 View
  16. Schäfer F, Faviez C, Voillot P, Foulquié P, Najm M, Jeanne J, Fagherazzi G, Schück S, Le Nevé B. Mapping and Modeling of Discussions Related to Gastrointestinal Discomfort in French-Speaking Online Forums: Results of a 15-Year Retrospective Infodemiology Study. Journal of Medical Internet Research 2020;22(11):e17247 View
  17. 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
  18. Petersen C, Halter R, Kotz D, Loeb L, Cook S, Pidgeon D, Christensen B, Batsis J. Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study. JMIR mHealth and uHealth 2020;8(8):e16862 View
  19. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  20. Sanders C, Nahar P, Small N, Hodgson D, Ong B, Dehghan A, Sharp C, Dixon W, Lewis S, Kontopantelis E, Daker-White G, Bower P, Davies L, Kayesh H, Spencer R, McAvoy A, Boaden R, Lovell K, Ainsworth J, Nowakowska M, Shepherd A, Cahoon P, Hopkins R, Allen D, Lewis A, Nenadic G. Digital methods to enhance the usefulness of patient experience data in services for long-term conditions: the DEPEND mixed-methods study. Health Services and Delivery Research 2020;8(28):1 View
  21. Yin Z, Sulieman L, Malin B. A systematic literature review of machine learning in online personal health data. Journal of the American Medical Informatics Association 2019;26(6):561 View
  22. Dehdarirad T, Freer J. Is there alignment amongst scientific literature, news media and patient forums regarding topics?: A study of breast and lung cancer. Online Information Review 2021;ahead-of-print(ahead-of-print) View
  23. Han X, Robinson L, Jensen R, Smith T, Yabroff K. Factors Associated With Health-Related Quality of Life Among Cancer Survivors in the United States. JNCI Cancer Spectrum 2021;5(1) View
  24. Al-Ramahi M, Elnoshokaty A, El-Gayar O, Nasralah T, Wahbeh A. Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data. JMIR Public Health and Surveillance 2021;7(4):e26780 View
  25. Schück S, Roustamal A, Gedik A, Voillot P, Foulquié P, Penfornis C, Job B. Assessing Patient Perceptions and Experiences of Paracetamol in France: Infodemiology Study Using Social Media Data Mining. Journal of Medical Internet Research 2021;23(7):e25049 View
  26. Fairie P, Zhang Z, D'Souza A, Walsh T, Quan H, Santana M. Categorising patient concerns using natural language processing techniques. BMJ Health & Care Informatics 2021;28(1):e100274 View
  27. Harrison C, Sidey-Gibbons C. Machine learning in medicine: a practical introduction to natural language processing. BMC Medical Research Methodology 2021;21(1) View