Published on in Vol 21, No 3 (2019): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12802, first published .
Artificial Intelligence and the Future of Primary Care: Exploratory Qualitative Study of UK General Practitioners’ Views

Artificial Intelligence and the Future of Primary Care: Exploratory Qualitative Study of UK General Practitioners’ Views

Artificial Intelligence and the Future of Primary Care: Exploratory Qualitative Study of UK General Practitioners’ Views

Journals

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  2. Doraiswamy P, Blease C, Bodner K. Artificial intelligence and the future of psychiatry: Insights from a global physician survey. Artificial Intelligence in Medicine 2020;102:101753 View
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  5. Rashid A. Yonder: Obesity communication, opioid deprescribing, actinic keratosis, and artificial intelligence. British Journal of General Practice 2019;69(684):350 View
  6. Kocaballi A, Ijaz K, Laranjo L, Quiroz J, Rezazadegan D, Tong H, Willcock S, Berkovsky S, Coiera E. Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners. Journal of the American Medical Informatics Association 2020;27(11):1695 View
  7. Gao S, He L, Chen Y, Li D, Lai K. Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media. Journal of Medical Internet Research 2020;22(7):e16649 View
  8. Hill A, Joyner C, Keith-Jopp C, Yet B, Tuncer Sakar C, Marsh W, Morrissey D. A Bayesian Network Decision Support Tool for Low Back Pain Using a RAND Appropriateness Procedure: Proposal and Internal Pilot Study. JMIR Research Protocols 2021;10(1):e21804 View
  9. Blease C, Kharko A, Locher C, DesRoches C, Mandl K, Marotta C. US primary care in 2029: A Delphi survey on the impact of machine learning. PLOS ONE 2020;15(10):e0239947 View
  10. Sandhu S, Lin A, Brajer N, Sperling J, Ratliff W, Bedoya A, Balu S, O'Brien C, Sendak M. Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study. Journal of Medical Internet Research 2020;22(11):e22421 View
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  12. Blease C, Locher C, Leon-Carlyle M, Doraiswamy M. Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey. DIGITAL HEALTH 2020;6:205520762096835 View
  13. Shinners L, Aggar C, Grace S, Smith S. Exploring healthcare professionals’ perceptions of artificial intelligence: Validating a questionnaire using the e-Delphi method. DIGITAL HEALTH 2021;7:205520762110034 View
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  15. Khullar D, Casalino L, Qian Y, Lu Y, Chang E, Aneja S. Public vs physician views of liability for artificial intelligence in health care. Journal of the American Medical Informatics Association 2021;28(7):1574 View
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  19. Wood E, Ange B, Miller D. Are We Ready to Integrate Artificial Intelligence Literacy into Medical School Curriculum: Students and Faculty Survey. Journal of Medical Education and Curricular Development 2021;8:238212052110240 View
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  22. Buck C, Doctor E, Hennrich J, Jöhnk J, Eymann T. General Practitioners’ Attitudes Toward Artificial Intelligence–Enabled Systems: Interview Study. Journal of Medical Internet Research 2022;24(1):e28916 View
  23. Terry A, Kueper J, Beleno R, Brown J, Cejic S, Dang J, Leger D, McKay S, Meredith L, Pinto A, Ryan B, Stewart M, Zwarenstein M, Lizotte D. Is primary health care ready for artificial intelligence? What do primary health care stakeholders say?. BMC Medical Informatics and Decision Making 2022;22(1) View
  24. Alqahtani A. A Review of the Scope, Future, and Effectiveness of Using Artificial Intelligence in Cardiac Rehabilitation: A Call to Action for the Kingdom of Saudi Arabia. Applied Artificial Intelligence 2023;37(1) View
  25. Siala H, Wang Y. SHIFTing artificial intelligence to be responsible in healthcare: A systematic review. Social Science & Medicine 2022;296:114782 View
  26. Shlivko I, Garanina O, Klemenova I, Uskova K, Mironycheva A, Dardyk V, Laskov V. Artificial intelligence: how it works and criteria for assessment. Consilium Medicum 2021;23(8):626 View
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  29. Scott I, Carter S, Coiera E. Exploring stakeholder attitudes towards AI in clinical practice. BMJ Health & Care Informatics 2021;28(1):e100450 View
  30. Blease C, Torous J, Dong Z, Davidge G, DesRoches C, Kharko A, Turner A, Jones R, Hägglund M, McMillan B. Patient Online Record Access in English Primary Care: Qualitative Survey Study of General Practitioners’ Views. Journal of Medical Internet Research 2023;25:e43496 View
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  34. d'Elia A, Gabbay M, Rodgers S, Kierans C, Jones E, Durrani I, Thomas A, Frith L. Artificial intelligence and health inequities in primary care: a systematic scoping review and framework. Family Medicine and Community Health 2022;10(Suppl 1):e001670 View
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  40. Čartolovni A, Tomičić A, Lazić Mosler E. Ethical, legal, and social considerations of AI-based medical decision-support tools: A scoping review. International Journal of Medical Informatics 2022;161:104738 View
  41. 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
  42. Chen M, Zhang B, Cai Z, Seery S, Gonzalez M, Ali N, Ren R, Qiao Y, Xue P, Jiang Y. Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey. Frontiers in Medicine 2022;9 View
  43. Mainous A. Will Technology and Artificial Intelligence Make the Primary Care Doctor Obsolete? Remember the Luddites. Frontiers in Medicine 2022;9 View
  44. Starke G, Schmidt B, De Clercq E, Elger B. Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry. AI and Ethics 2023;3(1):303 View
  45. Pan Y, Froese F. An interdisciplinary review of AI and HRM: Challenges and future directions. Human Resource Management Review 2023;33(1):100924 View
  46. McLennan S, Meyer A, Schreyer K, Buyx A, Sbaffi L. German medical students´ views regarding artificial intelligence in medicine: A cross-sectional survey. PLOS Digital Health 2022;1(10):e0000114 View
  47. Li B, de Mestral C, Mamdani M, Al-Omran M. Perceptions of Canadian vascular surgeons toward artificial intelligence and machine learning. Journal of Vascular Surgery Cases, Innovations and Techniques 2022;8(3):466 View
  48. Cárcamo Ibarra P, López González U, Esteban Hurtado A, Orrego Castro N, Diez Domingo S. Exploring the opinion of Spanish medical specialists about the usefulness of radiomics in oncology. Revista Española de Medicina Nuclear e Imagen Molecular (English Edition) 2023;42(4):231 View
  49. Ejikem M. Perspectives of Anesthesiologists Towards the Use of Artificial Intelligence in Anesthesia Practice in a Developing Country. Journal of Anesthesia and Surgical Research 2022 View
  50. Hogg H, Al-Zubaidy M, Talks J, Denniston A, Kelly C, Malawana J, Papoutsi C, Teare M, Keane P, Beyer F, Maniatopoulos G. Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence. Journal of Medical Internet Research 2023;25:e39742 View
  51. Hanis T, Islam M, Musa K. Diagnostic Accuracy of Machine Learning Models on Mammography in Breast Cancer Classification: A Meta-Analysis. Diagnostics 2022;12(7):1643 View
  52. Sangers T, Wakkee M, Moolenburgh F, Nijsten T, Lugtenberg M. Towards successful implementation of artificial intelligence in skin cancer care: a qualitative study exploring the views of dermatologists and general practitioners. Archives of Dermatological Research 2022 View
  53. Karimian G, Petelos E, Evers S. The ethical issues of the application of artificial intelligence in healthcare: a systematic scoping review. AI and Ethics 2022;2(4):539 View
  54. Mlodzinski E, Wardi G, Viglione C, Nemati S, Crotty Alexander L, Malhotra A. Assessing Barriers to Implementation of Machine Learning and Artificial Intelligence–Based Tools in Critical Care: Web-Based Survey Study. JMIR Perioperative Medicine 2023;6:e41056 View
  55. Ramessur R, Raja L, Kilduff C, Kang S, Li J, Thomas P, Sim D. Impact and Challenges of Integrating Artificial Intelligence and Telemedicine into Clinical Ophthalmology. Asia-Pacific Journal of Ophthalmology 2021;10(3):317 View
  56. Hospodková P, Berežná J, Barták M, Rogalewicz V, Severová L, Svoboda R. Change Management and Digital Innovations in Hospitals of Five European Countries. Healthcare 2021;9(11):1508 View
  57. Carboni C, Wehrens R, van der Veen R, de Bont A. Conceptualizing the digitalization of healthcare work: A metaphor-based Critical Interpretive Synthesis. Social Science & Medicine 2022;292:114572 View
  58. Willem T, Krammer S, Böhm A, French L, Hartmann D, Lasser T, Buyx A. Risks and benefits of dermatological machine learning health care applications—an overview and ethical analysis. Journal of the European Academy of Dermatology and Venereology 2022;36(9):1660 View
  59. Möllmann N, Mirbabaie M, Stieglitz S. Is it alright to use artificial intelligence in digital health? A systematic literature review on ethical considerations. Health Informatics Journal 2021;27(4):146045822110523 View
  60. Zipori A, Kerley C, Klein A, Kenney R. Real-World Translation of Artificial Intelligence in Neuro-Ophthalmology: The Challenges of Making an Artificial Intelligence System Applicable to Clinical Practice. Journal of Neuro-Ophthalmology 2022;42(3):287 View
  61. Frisinger A, Papachristou P. The voice of healthcare: introducing digital decision support systems into clinical practice - a qualitative study. BMC Primary Care 2023;24(1) View
  62. Henckert D, Malorgio A, Schweiger G, Raimann F, Piekarski F, Zacharowski K, Hottenrott S, Meybohm P, Tscholl D, Spahn D, Roche T. Attitudes of Anesthesiologists toward Artificial Intelligence in Anesthesia: A Multicenter, Mixed Qualitative–Quantitative Study. Journal of Clinical Medicine 2023;12(6):2096 View
  63. Weykamp M, Bingham J. Generation Learning Differences in Surgery. Surgical Clinics of North America 2023;103(2):287 View
  64. Al-Medfa M, Al-Ansari A, Darwish A, Qreeballa T, Jahrami H. Physicians’ attitudes and knowledge toward artificial intelligence in medicine: Benefits and drawbacks. Heliyon 2023;9(4):e14744 View
  65. Cárcamo Ibarra P, López González U, Esteban Hurtado A, Orrego Castro N, Diez Domingo S. Explorando la opinión de los especialistas españoles acerca de la utilidad de la radiómica en el área oncológica. Revista Española de Medicina Nuclear e Imagen Molecular 2023;42(4):231 View
  66. Sauerbrei A, Kerasidou A, Lucivero F, Hallowell N. The impact of artificial intelligence on the person-centred, doctor-patient relationship: some problems and solutions. BMC Medical Informatics and Decision Making 2023;23(1) View
  67. Painter A, Nix M, Verma J. Confidence in AI in general practice. Future Medicine AI 2023;1(2) View
  68. Tang L, Li J, Fantus S. Medical artificial intelligence ethics: A systematic review of empirical studies. DIGITAL HEALTH 2023;9 View
  69. Wewetzer L, Held L, Goetz K, Steinhäuser J. Determinants of the implementation of artificial intelligence-based screening for diabetic retinopathy—a cross-sectional study with general practitioners in Germany. DIGITAL HEALTH 2023;9:205520762311766 View
  70. Wiedermann C, Mahlknecht A, Piccoliori G, Engl A. Redesigning Primary Care: The Emergence of Artificial-Intelligence-Driven Symptom Diagnostic Tools. Journal of Personalized Medicine 2023;13(9):1379 View
  71. 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
  72. 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
  73. Hildebrand R, Chang D, Ewongwoo A, Ramchandran K, Gensheimer M. Study of Patient and Physician Attitudes Toward Automated Prognostic Models for Patients With Metastatic Cancer. JCO Clinical Cancer Informatics 2023;(7) View
  74. Rojahn J, Palu A, Skiena S, Jones J, Mahmoud A. American public opinion on artificial intelligence in healthcare. PLOS ONE 2023;18(11):e0294028 View
  75. Liu S, Wen A, Wang L, He H, Fu S, Miller R, Williams A, Harris D, Kavuluru R, Liu M, Abu-el-Rub N, Schutte D, Zhang R, Rouhizadeh M, Osborne J, He Y, Topaloglu U, Hong S, Saltz J, Schaffter T, Pfaff E, Chute C, Duong T, Haendel M, Fuentes R, Szolovits P, Xu H, Liu H. An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C). Journal of the American Medical Informatics Association 2023;30(12):2036 View
  76. Lin L, Tang B, Cao L, Yan J, Zhao T, Hua F, He H. The knowledge, experience, and attitude on artificial intelligence-assisted cephalometric analysis: Survey of orthodontists and orthodontic students. American Journal of Orthodontics and Dentofacial Orthopedics 2023;164(4):e97 View
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Books/Policy Documents

  1. Bohr A, Memarzadeh K. Artificial Intelligence in Healthcare. View
  2. Glauner P. Digitalization in Healthcare. View
  3. Hennrich J, Kauffmann A, Buck C, Eymann T. Künstliche Intelligenz im Gesundheitswesen. View
  4. Glauner P. Innovationen im Gesundheitswesen. View
  5. Yeats A. Deprescribing and Polypharmacy in an Aging Population. View
  6. Sides T, Farrell T, Kbaier D. HCI International 2023 Posters. View
  7. Sarkar P, Gopinath K, Prakash A. Transfer, Diffusion and Adoption of Next-Generation Digital Technologies. View