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

Pilot studies (ehealth) (206) Artificial Intelligence (1371) Participatory Medicine & E-Patients (773)

Published on in Vol 4, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16670, first published .
Patient Perception of Plain-Language Medical Notes Generated Using Artificial Intelligence Software: Pilot Mixed-Methods Study

Patient Perception of Plain-Language Medical Notes Generated Using Artificial Intelligence Software: Pilot Mixed-Methods Study

Patient Perception of Plain-Language Medical Notes Generated Using Artificial Intelligence Software: Pilot Mixed-Methods Study

Authors of this article:

Sandeep Bala1 Author Orcid Image ;   Angela Keniston2 Author Orcid Image ;   Marisha Burden2 Author Orcid Image
Article Authors Cited by (24) Tweetations (13) Metrics

Journals

  1. 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
  2. Mutasa S, Yi P. Clinical Artificial Intelligence Applications. Radiologic Clinics of North America 2021;59(6):1013 View
  3. Perlis N, Finelli A, Lovas M, Lund A, Di Meo A, Lajkosz K, Berlin A, Papadakos J, Ghai S, Deniffel D, Meng E, Wiljer D, Alibhai S, Bakas V, Badzynski A, Lee O, Cafazzo J, Haider M. Exploring the value of using patient-oriented MRI reports in clinical practice — a pilot study. Supportive Care in Cancer 2022;30(8):6857 View
  4. Solomonides A, Koski E, Atabaki S, Weinberg S, McGreevey J, Kannry J, Petersen C, Lehmann C. Defining AMIA’s artificial intelligence principles. Journal of the American Medical Informatics Association 2022;29(4):585 View
  5. Liu T, Xiao X. A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic. Frontiers in Public Health 2021;9 View
  6. Frommeyer T, Fursmidt R, Gilbert M, Bett E. The Desire of Medical Students to Integrate Artificial Intelligence Into Medical Education: An Opinion Article. Frontiers in Digital Health 2022;4 View
  7. Kelly M, Kieren M, Coller R, Pitt M, Smith C. Pediatric Open Notes: Caregiver Experiences Since the 21st Century Cures Act. Academic Pediatrics 2024;24(4):556 View
  8. Yang R, Tan T, Lu W, Thirunavukarasu A, Ting D, Liu N. Large language models in health care: Development, applications, and challenges. Health Care Science 2023;2(4):255 View
  9. van Mens H, Hannen G, Nienhuis R, Bolt R, de Keizer N, Cornet R. Evaluation of Patient-Friendly Diagnosis Clarifications in a Hospital Patient Portal. Applied Clinical Informatics 2023;14(03):455 View
  10. Yu P, Fang C, Liu X, Fu W, Ling J, Yan Z, Jiang Y, Cao Z, Wu M, Chen Z, Zhu W, Zhang Y, Abudukeremu A, Wang Y, Liu X, Wang J. Performance of ChatGPT on the Chinese Postgraduate Examination for Clinical Medicine: Survey Study. JMIR Medical Education 2024;10:e48514 View
  11. Stewart J, Lu J, Goudie A, Arendts G, Meka S, Freeman S, Walker K, Sprivulis P, Sanfilippo F, Bennamoun M, Dwivedi G, Reddy S. Applications of natural language processing at emergency department triage: A narrative review. PLOS ONE 2023;18(12):e0279953 View
  12. Nacht C, Jacobson N, Shiyanbola O, Smith C, Hoonakker P, Coller R, Dean S, Sklansky D, Smith W, Sprackling C, Kelly M. Perception of Physicians’ Notes Among Parents of Different Health Literacy Levels. Hospital Pediatrics 2024;14(2):108 View
  13. Katalinic M, Schenk M, Franke S, Katalinic A, Neumuth T, Dietz A, Stoehr M, Gaebel J. Generation of a Realistic Synthetic Laryngeal Cancer Cohort for AI Applications. Cancers 2024;16(3):639 View
  14. Zaretsky J, Kim J, Baskharoun S, Zhao Y, Austrian J, Aphinyanaphongs Y, Gupta R, Blecker S, Feldman J. Generative Artificial Intelligence to Transform Inpatient Discharge Summaries to Patient-Friendly Language and Format. JAMA Network Open 2024;7(3):e240357 View
  15. Frost E, Bosward R, Aquino Y, Braunack-Mayer A, Carter S. Facilitating public involvement in research about healthcare AI: A scoping review of empirical methods. International Journal of Medical Informatics 2024;186:105417 View
  16. Swanson K, He S, Calvano J, Chen D, Telvizian T, Jiang L, Chong P, Schwell J, Mak G, Lee J, Tariq A. Biomedical text readability after hypernym substitution with fine-tuned large language models. PLOS Digital Health 2024;3(4):e0000489 View
  17. Lee S. Association Between Korean Adults' Electronic Health Literacy and Active Participation in Health Decision-Making. CIN: Computers, Informatics, Nursing 2024 View
  18. Heinke A, Radgoudarzi N, Huang B, Baxter S. A review of ophthalmology education in the era of generative artificial intelligence. Asia-Pacific Journal of Ophthalmology 2024;13(4):100089 View
  19. Solmonovich R, Kouba I, Quezada O, Rodriguez-Ayala G, Rojas V, Bonilla K, Espino K, Bracero L. Artificial intelligence generates proficient Spanish obstetrics and gynecology counseling templates. AJOG Global Reports 2024;4(4):100400 View
  20. Muli I, Cajander Å, Hvitfeldt H, Lagerros Y, Söderberg D, Sjöblom L, Dahlgren A, Bertilson B, Farrokhnia N, Amer-Wåhlin I, Taloyan M, Hägglund M. To read or not to read – A cross-sectional study of Swedish primary care patients’ adoption of patient accessible electronic health records. DIGITAL HEALTH 2024;10 View
  21. Cao T, Chen Z, Nakayama M. Enhancing the Functionalities of Personal Health Record Systems: Empirical Study Based on the HL7 Personal Health Record System Functional Model Release 1. JMIR Medical Informatics 2024;12:e56735 View
  22. Lumbiganon S, Abou Chawareb E, Moukhtar Hammad M, Azad B, Shah D, Yafi F. Artificial Intelligence as a Tool for Creating Patient Visit Summary: A Scoping Review and Guide to Implementation in an Erectile Dysfunction Clinic. Current Urology Reports 2025;26(1) View

Books/Policy Documents

  1. . Building and Improving Health Literacy in the ‘New Normal’ of Health Care. View
  2. . Building and Improving Health Literacy in the ‘New Normal’ of Health Care. View