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

Books/Policy Documents

  1. Iqbal U, Arshed Ali Khan H, Li Y. Multiple Perspectives on Artificial Intelligence in Healthcare. View