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

Reviews in Medical Informatics (93) Artificial Intelligence (1371) Participatory Medicine & E-Patients (773)

Published on in Vol 7, No 2 (2019): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13445, first published .
The Use of Artificially Intelligent Self-Diagnosing Digital Platforms by the General Public: Scoping Review

The Use of Artificially Intelligent Self-Diagnosing Digital Platforms by the General Public: Scoping Review

The Use of Artificially Intelligent Self-Diagnosing Digital Platforms by the General Public: Scoping Review

Authors of this article:

Stephanie Aboueid1 Author Orcid Image ;   Rebecca H Liu2 Author Orcid Image ;   Binyam Negussie Desta1 Author Orcid Image ;   Ashok Chaurasia1 Author Orcid Image ;   Shanil Ebrahim3, 4 Author Orcid Image
Article Authors Cited by (41) Tweetations (8) Metrics

Journals

  1. Gottliebsen K, Petersson G. Limited evidence of benefits of patient operated intelligent primary care triage tools: findings of a literature review. BMJ Health & Care Informatics 2020;27(1):e100114 View
  2. Fiske A, Buyx A, Prainsack B. The double-edged sword of digital self-care: Physician perspectives from Northern Germany. Social Science & Medicine 2020;260:113174 View
  3. Morse K, Ostberg N, Jones V, Chan A. Use Characteristics and Triage Acuity of a Digital Symptom Checker in a Large Integrated Health System: Population-Based Descriptive Study. Journal of Medical Internet Research 2020;22(11):e20549 View
  4. Aboueid S, Meyer S, Wallace J, Mahajan S, Nur T, Chaurasia A. Use of symptom checkers for COVID-19-related symptoms among university students: a qualitative study. BMJ Innovations 2021;7(2):253 View
  5. Ćirković A. Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study. Journal of Medical Internet Research 2020;22(12):e18097 View
  6. Aboueid S, Meyer S, Wallace J, Mahajan S, Chaurasia A. Young Adults’ Perspectives on the Use of Symptom Checkers for Self-Triage and Self-Diagnosis: Qualitative Study. JMIR Public Health and Surveillance 2021;7(1):e22637 View
  7. Char D, Abràmoff M, Feudtner C. Identifying Ethical Considerations for Machine Learning Healthcare Applications. The American Journal of Bioethics 2020;20(11):7 View
  8. Drydakis N. Mobile applications aiming to facilitate immigrants’ societal integration and overall level of integration, health and mental health. Does artificial intelligence enhance outcomes?. Computers in Human Behavior 2021;117:106661 View
  9. Ceney A, Tolond S, Glowinski A, Marks B, Swift S, Palser T, Wilson F. Accuracy of online symptom checkers and the potential impact on service utilisation. PLOS ONE 2021;16(7):e0254088 View
  10. Wetzel A, Koch R, Preiser C, Müller R, Klemmt M, Ranisch R, Ehni H, Wiesing U, Rieger M, Henking T, Joos S. Ethical, Legal, and Social Implications of Symptom Checker Apps in Primary Health Care (CHECK.APP): Protocol for an Interdisciplinary Mixed Methods Study. JMIR Research Protocols 2022;11(5):e34026 View
  11. Aboueid S, Meyer S, Wallace J, Chaurasia A, Dragan D. Latent classes associated with the intention to use a symptom checker for self-triage. PLOS ONE 2021;16(11):e0259547 View
  12. Ruyobeza B, Grobbelaar S, Botha A. Hurdles to developing and scaling remote patients’ health management tools and systems: a scoping review. Systematic Reviews 2022;11(1) View
  13. Drydakis N. M-health Apps and Physical and Mental Health Outcomes of Sexual Minorities. Journal of Homosexuality 2023;70(14):3421 View
  14. Zigarelli A, Jia Z, Lee H. Machine-Aided Self-diagnostic Prediction Models for Polycystic Ovary Syndrome: Observational Study. JMIR Formative Research 2022;6(3):e29967 View
  15. Ho A. Can Public Health Investment and Oversight save Digital Mental Health?. AJOB Neuroscience 2022;13(3):201 View
  16. Pairon A, Philips H, Verhoeven V. A scoping review on the use and usefulness of online symptom checkers and triage systems: How to proceed?. Frontiers in Medicine 2023;9 View
  17. Müller R, Klemmt M, Ehni H, Henking T, Kuhnmünch A, Preiser C, Koch R, Ranisch R. Ethical, legal, and social aspects of symptom checker applications: a scoping review. Medicine, Health Care and Philosophy 2022;25(4):737 View
  18. Turner J, Knowles E, Simpson R, Sampson F, Dixon S, Long J, Bell-Gorrod H, Jacques R, Coster J, Yang H, Nicholl J, Bath P, Fall D, Stone T. Impact of NHS 111 Online on the NHS 111 telephone service and urgent care system: a mixed-methods study. Health Services and Delivery Research 2021;9(21):1 View
  19. Arellano Carmona K, Chittamuru D, Kravitz R, Ramondt S, Ramírez A. Health Information Seeking From an Intelligent Web-Based Symptom Checker: Cross-sectional Questionnaire Study. Journal of Medical Internet Research 2022;24(8):e36322 View
  20. Millen E, Salim N, Azadzoy H, Bane M, O'Donnell L, Schmude M, Bode P, Tuerk E, Vaidya R, Gilbert S. Study protocol for a pilot prospective, observational study investigating the condition suggestion and urgency advice accuracy of a symptom assessment app in sub-Saharan Africa: the AFYA-‘Health’ Study. BMJ Open 2022;12(4):e055915 View
  21. Ben-Shabat N, Sharvit G, Meimis B, Ben Joya D, Sloma A, Kiderman D, Shabat A, Tsur A, Watad A, Amital H. Assessing data gathering of chatbot based symptom checkers - a clinical vignettes study. International Journal of Medical Informatics 2022;168:104897 View
  22. Alonto A, Apor A, Jamora R. Burden of Neurological Diseases in the Philippines as Revealed by Web Searches: An Infodemiological Study. International Journal of Environmental Research and Public Health 2022;19(24):16736 View
  23. Benoit J, Hartling L, Scott S. Bridging evidence-to-care gaps with mHealth: Designing a symptom checker for parents accessing knowledge translation resources on acute children’s illnesses in a smartphone application. PEC Innovation 2023;2:100152 View
  24. Maican C, Sumedrea S, Tecau A, Nichifor E, Chitu I, Lixandroiu R, Bratucu G. Factors Influencing the Behavioural Intention to Use AI-Generated Images in Business. Journal of Organizational and End User Computing 2023;35(1):1 View
  25. Radionova N, Ög E, Wetzel A, Rieger M, Preiser C. Impacts of Symptom Checkers for Laypersons’ Self-diagnosis on Physicians in Primary Care: Scoping Review. Journal of Medical Internet Research 2023;25:e39219 View
  26. Kuroiwa T, Sarcon A, Ibara T, Yamada E, Yamamoto A, Tsukamoto K, Fujita K. The Potential of ChatGPT as a Self-Diagnostic Tool in Common Orthopedic Diseases: Exploratory Study. Journal of Medical Internet Research 2023;25:e47621 View
  27. Wetzel A, Klemmt M, Müller R, Rieger M, Joos S, Koch R. Only the anxious ones? Identifying characteristics of symptom checker app users: a cross-sectional survey. BMC Medical Informatics and Decision Making 2024;24(1) View
  28. Gad H, Kalra S, Pinzon R, Garcia R, Yotsombut K, Coetzee A, Nafach J, Lim L, Fletcher P, Lim V, Malik R. Earlier diagnosis of peripheral neuropathy in primary care: A call to action. Journal of the Peripheral Nervous System 2024;29(1):28 View
  29. 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
  30. Hammoud M, Douglas S, Darmach M, Alawneh S, Sanyal S, Kanbour Y. Evaluating the Diagnostic Performance of Symptom Checkers: Clinical Vignette Study. JMIR AI 2024;3:e46875 View
  31. Becker M, Matt C. How individuals perceive and process diagnostic device errors. Journal of Decision Systems 2024:1 View
  32. Kopka M, Feufel M. Software symptomcheckR: an R package for analyzing and visualizing symptom checker triage performance. BMC Digital Health 2024;2(1) View
  33. Aissaoui Ferhi L, Ben Amar M, Choubani F, Bouallegue R. Empowering Medical Diagnosis: A Machine Learning Approach for Symptom-Based Health Checker. Mobile Networks and Applications 2024 View
  34. North F, Buss R, Nelson E, Thompson M, Pecina J, Crum B. Patient Opportunities to Self-Schedule in a Large Multisite, Multispecialty Medical Practice: Program Description and Uptake of 7 Unique Processes for Patients to Successfully Self-Schedule (and Reschedule) Their Medical Appointments. Health Services Research and Managerial Epidemiology 2024;11 View
  35. Rizwan B, Weigle P. Paging Dr Influencer. Pediatric Clinics of North America 2024 View
  36. Preiser C, Radionova N, Ög E, Koch R, Klemmt M, Müller R, Ranisch R, Joos S, Rieger M. The Doctors, Their Patients, and the Symptom Checker App: Qualitative Interview Study With General Practitioners in Germany. JMIR Human Factors 2024;11:e57360 View

Books/Policy Documents

  1. Schneider P, Xhafa F. Anomaly Detection and Complex Event Processing over IoT Data Streams. View
  2. Kalpana , Srivastava A, Jha S. Predictive Modeling in Biomedical Data Mining and Analysis. View
  3. Rusko R, Koivisto S, Jestilä S. Analytics Enabled Decision Making. View
  4. Gerke S. Digital Health Care outside of Traditional Clinical Settings. View