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

Articles* (13) Artificial Intelligence (1421)

Published on in Vol 8, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21056, first published .
Impact of a Commercial Artificial Intelligence–Driven Patient Self-Assessment Solution on Waiting Times at General Internal Medicine Outpatient Departments: Retrospective Study

Impact of a Commercial Artificial Intelligence–Driven Patient Self-Assessment Solution on Waiting Times at General Internal Medicine Outpatient Departments: Retrospective Study

Impact of a Commercial Artificial Intelligence–Driven Patient Self-Assessment Solution on Waiting Times at General Internal Medicine Outpatient Departments: Retrospective Study

Authors of this article:

Yukinori Harada1, 2 Author Orcid Image ;   Taro Shimizu1 Author Orcid Image
Article Authors Cited by (13) Tweetations (3) Metrics

Journals

  1. Harada Y, Katsukura S, Kawamura R, Shimizu T. Efficacy of Artificial-Intelligence-Driven Differential-Diagnosis List on the Diagnostic Accuracy of Physicians: An Open-Label Randomized Controlled Study. International Journal of Environmental Research and Public Health 2021;18(4):2086 View
  2. Nishida A, Ogawa O. The Effect of a Pre-consultation Tablet-Based Questionnaire on Changes in Consultation Time for First-Visit Patients With Diabetes: A Single-Case Design Preliminary Study. Cureus 2022 View
  3. Asai A, Konno M, Taniguchi M, Vecchione A, Ishii H. Computational healthcare: Present and future perspectives (Review). Experimental and Therapeutic Medicine 2021;22(6) View
  4. Kawamura R, Harada Y, Sugimoto S, Nagase Y, Katsukura S, Shimizu T. Incidence of Diagnostic Errors Among Unexpectedly Hospitalized Patients Using an Automated Medical History–Taking System With a Differential Diagnosis Generator: Retrospective Observational Study. JMIR Medical Informatics 2022;10(1):e35225 View
  5. Harada Y, Tomiyama S, Sakamoto T, Sugimoto S, Kawamura R, Yokose M, Hayashi A, Shimizu T. Effects of Combinational Use of Additional Differential Diagnostic Generators on the Diagnostic Accuracy of the Differential Diagnosis List Developed by an Artificial Intelligence–Driven Automated History–Taking System: Pilot Cross-Sectional Study. JMIR Formative Research 2023;7:e49034 View
  6. 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
  7. Pedro A, Dias M, Laranjo L, Cunha A, Cordeiro J, Adebisi J. Artificial intelligence in medicine: A comprehensive survey of medical doctor’s perspectives in Portugal. PLOS ONE 2023;18(9):e0290613 View
  8. Zhakhina G, Tapinova K, Kanabekova P, Kainazarov T. Pre-consultation history taking systems and their impact on modern practices: Advantages and limitations. Journal of Clinical Medicine of Kazakhstan 2023;20(6):26 View
  9. Palermi S, Vecchiato M, Saglietto A, Niederseer D, Oxborough D, Ortega-Martorell S, Olier I, Castelletti S, Baggish A, Maffessanti F, Biffi A, D’Andrea A, Zorzi A, Cavarretta E, D’Ascenzi F. Unlocking the potential of artificial intelligence in sports cardiology: does it have a role in evaluating athlete’s heart?. European Journal of Preventive Cardiology 2024;31(4):470 View
  10. Harada Y, Sakamoto T, Sugimoto S, Shimizu T. Longitudinal Changes in Diagnostic Accuracy of a Differential Diagnosis List Developed by an AI-Based Symptom Checker: Retrospective Observational Study. JMIR Formative Research 2024;8:e53985 View
  11. Gibelli F, Bailo P, Pesel G, Ricci G. Preserving Patient Stories: Bioethical and Legal Implications Related to the Shift from Traditional to Digital Anamnesis. Clinics and Practice 2024;14(4):1196 View
  12. Sakamoto T, Harada Y, Shimizu T. Facilitating Trust Calibration in Artificial Intelligence–Driven Diagnostic Decision Support Systems for Determining Physicians’ Diagnostic Accuracy: Quasi-Experimental Study. JMIR Formative Research 2024;8:e58666 View
  13. Haq M, Derhab M, Saeed R, Khan H, Mushhood Ur Rehman M. Revolutionizing Acute Stroke Care: A Review of Food and Drug Administration-Approved Software as Medical Devices for Stroke Triage. Cureus 2024 View