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

Participatory Medicine & E-Patients (758) Information Retrieval (271) Information Seeking, Information Needs (424)

Published on in Vol 22, No 3 (2020): March

Assessment of the Frequency of Online Searches for Symptoms Before Diagnosis: Analysis of Archival Data

Assessment of the Frequency of Online Searches for Symptoms Before Diagnosis: Analysis of Archival Data

Assessment of the Frequency of Online Searches for Symptoms Before Diagnosis: Analysis of Archival Data

Authors of this article:

Irit Hochberg1, 2 Author Orcid Image ;   Raviv Allon2 Author Orcid Image ;   Elad Yom-Tov3, 4 Author Orcid Image
Article Authors Cited by (23) Tweetations (15) Metrics

Journals

  1. Hochberg I, Orshalimy S, Yom-Tov E. Real-World Evidence on the Effect of Missing an Oral Contraceptive Dose: Analysis of Internet Search Engine Queries. Journal of Medical Internet Research 2020;22(9):e20632 View
  2. Yom-Tov E, Cherlow Y. Ethical Challenges and Opportunities Associated With the Ability to Perform Medical Screening From Interactions With Search Engines: Viewpoint. Journal of Medical Internet Research 2020;22(9):e21922 View
  3. ESEN M. COVID-19 salgınıyla ilişkili semptomların Türkiye’den gerçekleştirilen internet arama motoru sorgularının incelenmesi. Journal of Medicine and Palliative Care 2021;2(1):7 View
  4. Ilias I, Milionis C, Koukkou E. COVID-19 and thyroid disease: An infodemiological pilot study. World Journal of Methodology 2022;12(3):99 View
  5. De Silva L, Baysari M, Keep M, Kench P, Clarke J. Patient requests for radiological services: An Australian study of patient agency and the impact of online health information. Health Promotion Journal of Australia 2023;34(2):437 View
  6. 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
  7. Uddin Quadery S, Hasan M, Khan M. Consumer side economic perception of telemedicine during COVID-19 era: A survey on Bangladesh's perspective. Informatics in Medicine Unlocked 2021;27:100797 View
  8. Jamuar S, Palmer R, Dawkins H, Lee D, Helmholz P, Baynam G, Wong A. 3D facial analysis for rare disease diagnosis and treatment monitoring: Proof-Of-Concept plan for hereditary angioedema. PLOS Digital Health 2023;2(3):e0000090 View
  9. Liu V, Koskela T, Kaila M. User-Initiated Symptom Assessment With an Electronic Symptom Checker: Protocol for a Mixed Methods Validation Study. JMIR Research Protocols 2023;12:e41423 View
  10. Chakraborty C, Bhattacharya M, Lee S. Need an AI-Enabled, Next-Generation, Advanced ChatGPT or Large Language Models (LLMs) for Error-Free and Accurate Medical Information. Annals of Biomedical Engineering 2024;52(2):134 View
  11. Pushpanathan K, Lim Z, Er Yew S, Chen D, Hui'En Lin H, Lin Goh J, Wong W, Wang X, Jin Tan M, Chang Koh V, Tham Y. Popular large language model chatbots’ accuracy, comprehensiveness, and self-awareness in answering ocular symptom queries. iScience 2023;26(11):108163 View
  12. Kanbach D, Heiduk L, Blueher G, Schreiter M, Lahmann A. The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective. Review of Managerial Science 2024;18(4):1189 View
  13. Moorman C, van Heerde H, Moreau C, Palmatier R. Marketing in the Health Care Sector: Disrupted Exchanges and New Research Directions. Journal of Marketing 2024;88(1):1 View
  14. Bachl M, Link E, Mangold F, Stier S. Search Engine Use for Health-Related Purposes: Behavioral Data on Online Health Information-Seeking in Germany. Health Communication 2024;39(8):1651 View
  15. Wimbarti S, Kairupan B, Tallei T. Critical review of self‐diagnosis of mental health conditions using artificial intelligence. International Journal of Mental Health Nursing 2024;33(2):344 View
  16. Chakraborty C, Pal S, Bhattacharya M, Islam M. AI-enabled ChatGPT’s carbon footprint and its use in the healthcare sector: a coin has two sides. International Journal of Surgery 2024;110(2):1306 View
  17. Farook T, Haq T, Dudley J. Dental loop signals: Image-to-signal processing for mandibular electromyography. Software Impacts 2024;19:100631 View
  18. Farook T, Haq T, Ramees L, Dudley J. Deep learning and predictive modelling for generating normalised muscle function parameters from signal images of mandibular electromyography. Medical & Biological Engineering & Computing 2024;62(6):1763 View
  19. Alsabhan J, Almalag H, Abanmy N, Aljadeed Y, Alhassan R, Albaker A. A content-quality and optimization analysis of YouTube as a source of patient information for bipolar disorder. Saudi Pharmaceutical Journal 2024;32(4):101997 View
  20. Carnino J, Pellegrini W, Willis M, Cohen M, Paz-Lansberg M, Davis E, Grillone G, Levi J. Assessing ChatGPT’s Responses to Otolaryngology Patient Questions. Annals of Otology, Rhinology & Laryngology 2024;133(7):658 View

Books/Policy Documents

  1. Mejova Y. Handbook of Computational Social Science for Policy. View
  2. Di Nunzio G, Vezzani F. Experimental IR Meets Multilinguality, Multimodality, and Interaction. View
  3. Yang A, Lebedoff S. Clinical Health Psychology in Military and Veteran Settings. View