Published on in Vol 22, No 1 (2020): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14679, first published .
Patient Perspectives on the Usefulness of an Artificial Intelligence–Assisted Symptom Checker: Cross-Sectional Survey Study

Patient Perspectives on the Usefulness of an Artificial Intelligence–Assisted Symptom Checker: Cross-Sectional Survey Study

Patient Perspectives on the Usefulness of an Artificial Intelligence–Assisted Symptom Checker: Cross-Sectional Survey Study

Journals

  1. Miller S, Gilbert S, Virani V, Wicks P. Patients’ Utilization and Perception of an Artificial Intelligence–Based Symptom Assessment and Advice Technology in a British Primary Care Waiting Room: Exploratory Pilot Study. JMIR Human Factors 2020;7(3):e19713 View
  2. Dunn A. Will online symptom checkers improve health care in Australia?. Medical Journal of Australia 2020;212(11):512 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, 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
  5. Schmieding M, Mörgeli R, Schmieding M, Feufel M, Balzer F. Benchmarking Triage Capability of Symptom Checkers Against That of Medical Laypersons: Survey Study. Journal of Medical Internet Research 2021;23(3):e24475 View
  6. Warden T, Oswald F, Roth E, Argall B, Barry B, Carayon P, Czaja S, Ratwani R. The National Academies Board on Human System Integration (BOHSI) Panel: Promise, Progress and Challenges of Leveraging AI Technology in Healthcare. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2020;64(1):2124 View
  7. Rigamonti L, Estel K, Gehlen T, Wolfarth B, Lawrence J, Back D. Use of artificial intelligence in sports medicine: a report of 5 fictional cases. BMC Sports Science, Medicine and Rehabilitation 2021;13(1) View
  8. Jones O, Calanzani N, Saji S, Duffy S, Emery J, Hamilton W, Singh H, de Wit N, Walter F. Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review. Journal of Medical Internet Research 2021;23(3):e23483 View
  9. 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
  10. Montazeri M, Multmeier J, Novorol C, Upadhyay S, Wicks P, Gilbert S. Optimization of Patient Flow in Urgent Care Centers Using a Digital Tool for Recording Patient Symptoms and History: Simulation Study. JMIR Formative Research 2021;5(5):e26402 View
  11. 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
  12. Fagni F, Knitza J, Krusche M, Kleyer A, Tascilar K, Simon D. Digital Approaches for a Reliable Early Diagnosis of Psoriatic Arthritis. Frontiers in Medicine 2021;8 View
  13. 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
  14. Graber M. Reaching 95%: decision support tools are the surest way to improve diagnosis now. BMJ Quality & Safety 2022;31(6):415 View
  15. Gräf M, Knitza J, Leipe J, Krusche M, Welcker M, Kuhn S, Mucke J, Hueber A, Hornig J, Klemm P, Kleinert S, Aries P, Vuillerme N, Simon D, Kleyer A, Schett G, Callhoff J. Comparison of physician and artificial intelligence-based symptom checker diagnostic accuracy. Rheumatology International 2022;42(12):2167 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. Martínez-García M, Hernández-Lemus E. Data Integration Challenges for Machine Learning in Precision Medicine. Frontiers in Medicine 2022;8 View
  18. van Bussel M, Odekerken–Schröder G, Ou C, Swart R, Jacobs M. Analyzing the determinants to accept a virtual assistant and use cases among cancer patients: a mixed methods study. BMC Health Services Research 2022;22(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. 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
  21. Young A, Amara D, Bhattacharya A, Wei M. Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review. The Lancet Digital Health 2021;3(9):e599 View
  22. Jeyakumar T, Younus S, Zhang M, Clare M, Charow R, Karsan I, Dhalla A, Al-Mouaswas D, Scandiffio J, Aling J, Salhia M, Lalani N, Overholt S, Wiljer D. Preparing for an Artificial Intelligence–Enabled Future: Patient Perspectives on Engagement and Health Care Professional Training for Adopting Artificial Intelligence Technologies in Health Care Settings. JMIR AI 2023;2:e40973 View
  23. Fritsch S, Blankenheim A, Wahl A, Hetfeld P, Maassen O, Deffge S, Kunze J, Rossaint R, Riedel M, Marx G, Bickenbach J. Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients. DIGITAL HEALTH 2022;8:205520762211167 View
  24. Gilbert S, Fenech M, Upadhyay S, Wicks P, Novorol C. Quality of condition suggestions and urgency advice provided by the Ada symptom assessment app evaluated with vignettes optimised for Australia. Australian Journal of Primary Health 2021;27(5):377 View
  25. Chalutz Ben-Gal H. Artificial intelligence (AI) acceptance in primary care during the coronavirus pandemic: What is the role of patients' gender, age and health awareness? A two-phase pilot study. Frontiers in Public Health 2023;10 View
  26. Patel R, Swanton A, Gross M. Online Symptom Checkers are Poor Tools for Diagnosing Men's Health Conditions. Urology 2022;170:124 View
  27. Judson T, Pierce L, Tutman A, Mourad M, Neinstein A, Shuler G, Gonzales R, Odisho A. Utilization patterns and efficiency gains from use of a fully EHR-integrated COVID-19 self-triage and self-scheduling tool: a retrospective analysis. Journal of the American Medical Informatics Association 2022;29(12):2066 View
  28. 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
  29. Kopka M, Schmieding M, Rieger T, Roesler E, Balzer F, Feufel M. Determinants of Laypersons’ Trust in Medical Decision Aids: Randomized Controlled Trial. JMIR Human Factors 2022;9(2):e35219 View
  30. Kopka M, Feufel M, Balzer F, Schmieding M. The Triage Capability of Laypersons: Retrospective Exploratory Analysis. JMIR Formative Research 2022;6(10):e38977 View
  31. Khanijahani A, Iezadi S, Dudley S, Goettler M, Kroetsch P, Wise J. Organizational, professional, and patient characteristics associated with artificial intelligence adoption in healthcare: A systematic review. Health Policy and Technology 2022;11(1):100602 View
  32. Woodcock C, Mittelstadt B, Busbridge D, Blank G. The Impact of Explanations on Layperson Trust in Artificial Intelligence–Driven Symptom Checker Apps: Experimental Study. Journal of Medical Internet Research 2021;23(11):e29386 View
  33. McCool J, Dobson R, Whittaker R, Paton C. Mobile Health (mHealth) in Low- and Middle-Income Countries. Annual Review of Public Health 2022;43(1):525 View
  34. Hennemann S, Kuhn S, Witthöft M, Jungmann S. Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients. JMIR Mental Health 2022;9(1):e32832 View
  35. Salwei M, Carayon P. A Sociotechnical Systems Framework for the Application of Artificial Intelligence in Health Care Delivery. Journal of Cognitive Engineering and Decision Making 2022;16(4):194 View
  36. Abensur Vuillaume L, Turpinier J, Cipolat L, Arnaud-Dépil-Duval , Dumontier T, Peschanski N, Kieffer Y, Barbat B, Riquier T, Dinot V, Galland J, Piryani R. Exploratory study: Evaluation of a symptom checker effectiveness for providing a diagnosis and evaluating the situation emergency compared to emergency physicians using simulated and standardized patients. PLOS ONE 2023;18(2):e0277568 View
  37. Scott I. Using information technology to reduce diagnostic error: still a bridge too far?. Internal Medicine Journal 2022;52(6):908 View
  38. Cowan R, Rapoport A, Blythe J, Rothrock J, Knievel K, Peretz A, Ekpo E, Sanjanwala B, Woldeamanuel Y. Diagnostic accuracy of an artificial intelligence online engine in migraine: A multi‐center study. Headache: The Journal of Head and Face Pain 2022;62(7):870 View
  39. Chan F, Lai S, Pieterman M, Richardson L, Singh A, Peters J, Toy A, Piccininni C, Rouault T, Wong K, Quong J, Wakabayashi A, Pawelec-Brzychczy A, Gruneir A. Performance of a new symptom checker in patient triage: Canadian cohort study. PLOS ONE 2021;16(12):e0260696 View
  40. Knitza J, Muehlensiepen F, Ignatyev Y, Fuchs F, Mohn J, Simon D, Kleyer A, Fagni F, Boeltz S, Morf H, Bergmann C, Labinsky H, Vorbrüggen W, Ramming A, Distler J, Bartz-Bazzanella P, Vuillerme N, Schett G, Welcker M, Hueber A. Patient's Perception of Digital Symptom Assessment Technologies in Rheumatology: Results From a Multicentre Study. Frontiers in Public Health 2022;10 View
  41. Schmieding M, Kopka M, Schmidt K, Schulz-Niethammer S, Balzer F, Feufel M. Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation. Journal of Medical Internet Research 2022;24(5):e31810 View
  42. Kujala S, Hörhammer I. Health Care Professionals’ Experiences of Web-Based Symptom Checkers for Triage: Cross-sectional Survey Study. Journal of Medical Internet Research 2022;24(5):e33505 View
  43. Pelly M, Fatehi F, Liew D, Verdejo-Garcia A. Artificial intelligence for secondary prevention of myocardial infarction: A qualitative study of patient and health professional perspectives. International Journal of Medical Informatics 2023;173:105041 View
  44. Nurek M, Kostopoulou O. How the UK public views the use of diagnostic decision aids by physicians: a vignette-based experiment. Journal of the American Medical Informatics Association 2023;30(5):888 View
  45. 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
  46. Ebbert J, Khan R, Leibovich B. Health Care Transformations Merging Traditional and Digital Medical Practices. Mayo Clinic Proceedings: Digital Health 2023;1(2):63 View
  47. Riboli-Sasco E, El-Osta A, Alaa A, Webber I, Karki M, El Asmar M, Purohit K, Painter A, Hayhoe B. Triage and Diagnostic Accuracy of Online Symptom Checkers: Systematic Review. Journal of Medical Internet Research 2023;25:e43803 View
  48. Kopka M, Scatturin L, Napierala H, Fürstenau D, Feufel M, Balzer F, Schmieding M. Characteristics of Users and Nonusers of Symptom Checkers in Germany: Cross-Sectional Survey Study. Journal of Medical Internet Research 2023;25:e46231 View
  49. Deng Z, Tian Z, Xue J, Gupta S. What predicts patients’ satisfaction and continuous use of intelligent medical guidance? the moderating effect of consulting experience. Behaviour & Information Technology 2023:1 View
  50. 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
  51. Mäkitie A, Alabi R, Ng S, Takes R, Robbins K, Ronen O, Shaha A, Bradley P, Saba N, Nuyts S, Triantafyllou A, Piazza C, Rinaldo A, Ferlito A. Artificial Intelligence in Head and Neck Cancer: A Systematic Review of Systematic Reviews. Advances in Therapy 2023;40(8):3360 View
  52. Kanazawa A, Fujibayashi K, Watanabe Y, Kushiro S, Yanagisawa N, Fukataki Y, Kitamura S, Hayashi W, Nagao M, Nishizaki Y, Inomata T, Arikawa-Hirasawa E, Naito T. Evaluation of a Medical Interview-Assistance System Using Artificial Intelligence for Resident Physicians Interviewing Simulated Patients: A Crossover, Randomized, Controlled Trial. International Journal of Environmental Research and Public Health 2023;20(12):6176 View
  53. Hameed B, Naik N, Ibrahim S, Tatkar N, Shah M, Prasad D, Hegde P, Chlosta P, Rai B, Somani B. Breaking Barriers: Unveiling Factors Influencing the Adoption of Artificial Intelligence by Healthcare Providers. Big Data and Cognitive Computing 2023;7(2):105 View
  54. Vo V, Chen G, Aquino Y, Carter S, Do Q, Woode M. Multi-stakeholder preferences for the use of artificial intelligence in healthcare: A systematic review and thematic analysis. Social Science & Medicine 2023;338:116357 View
  55. Peven K, Wickham A, Wilks O, Kaplan Y, Marhol A, Ahmed S, Bamford R, Cunningham A, Prentice C, Meczner A, Fenech M, Gilbert S, Klepchukova A, Ponzo S, Zhaunova L. Assessment of a Digital Symptom Checker Tool's Accuracy in Suggesting Reproductive Health Conditions: Clinical Vignettes Study. JMIR mHealth and uHealth 2023;11:e46718 View
  56. Fazakarley C, Breen M, Leeson P, Thompson B, Williamson V. Experiences of using artificial intelligence in healthcare: a qualitative study of UK clinician and key stakeholder perspectives. BMJ Open 2023;13(12):e076950 View
  57. 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
  58. Fazakarley C, Breen M, Thompson B, Leeson P, Williamson V. Beliefs, experiences and concerns of using artificial intelligence in healthcare: A qualitative synthesis. DIGITAL HEALTH 2024;10 View
  59. Curioso W, Coronel-Chucos L, Oscuvilca-Tapia E. Empowering the digital health workforce in Latin America in the context of the COVID-19 pandemic: the Peruvian case. Informatics for Health and Social Care 2024;49(1):73 View
  60. Müller R, Klemmt M, Koch R, Ehni H, Henking T, Langmann E, Wiesing U, Ranisch R. “That’s just Future Medicine” - a qualitative study on users’ experiences of symptom checker apps. BMC Medical Ethics 2024;25(1) View
  61. 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
  62. Wetzel A, Koch R, Koch N, Klemmt M, Müller R, Preiser C, Rieger M, Rösel I, Ranisch R, Ehni H, Joos S. ‘Better see a doctor?’ Status quo of symptom checker apps in Germany: A cross-sectional survey with a mixed-methods design (CHECK.APP). DIGITAL HEALTH 2024;10 View
  63. Yan S, Liu Y, Ma L, Xiao L, Hu X, Guo R, You C, Tian R. Walking forward or on hold: Could the ChatGPT be applied for seeking health information in neurosurgical settings?. Ibrain 2024;10(1):111 View
  64. Monteith S, Glenn T, Geddes J, Whybrow P, Achtyes E, Bauer M. Implications of Online Self-Diagnosis in Psychiatry. Pharmacopsychiatry 2024;57(02):45 View
  65. Savolainen K, Kujala S. Testing Two Online Symptom Checkers With Vulnerable Groups: Usability Study to Improve Cognitive Accessibility of eHealth Services. JMIR Human Factors 2024;11:e45275 View
  66. Zawati M, Lang M. Does an App a Day Keep the Doctor Away?: AI Symptom Checker Applications, Entrenched Bias, and Professional Responsibility (Preprint). Journal of Medical Internet Research 2023 View
  67. Privitera A, Ng S, Kong A, Weekes B. AI and Aphasia in the Digital Age: A Critical Review. Brain Sciences 2024;14(4):383 View
  68. Miller N, North F, Curry E, Thompson M, Pecina J. Recommendation endpoints and safety of an online self-triage for depression symptoms. Journal of Telemedicine and Telecare 2024 View

Books/Policy Documents

  1. Iqbal U, Arshed Ali Khan H, Li Y. Multiple Perspectives on Artificial Intelligence in Healthcare. View
  2. Ghosh K, Sharma S, Sarkar S, Kaushik A. Advances in Data Science and Computing Technologies. View
  3. Gerke S. Digital Health Care outside of Traditional Clinical Settings. View