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

Research Letter (7) New Methods and Approaches in Medical Education (316) Clinical Information and Decision Making (1678) Imaging Informatics (237) Artificial Intelligence (1766) Machine Learning (1759)

Published on in Vol 10 (2024)

This is a member publication of University College London (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52155, first published .
Using AI Text-to-Image Generation to Create Novel Illustrations for Medical Education: Current Limitations as Illustrated by Hypothyroidism and Horner Syndrome

Using AI Text-to-Image Generation to Create Novel Illustrations for Medical Education: Current Limitations as Illustrated by Hypothyroidism and Horner Syndrome

Using AI Text-to-Image Generation to Create Novel Illustrations for Medical Education: Current Limitations as Illustrated by Hypothyroidism and Horner Syndrome

Authors of this article:

Ajay Kumar1 Author Orcid Image ;   Pierce Burr1 Author Orcid Image ;   Tim Michael Young1 Author Orcid Image
Article Authors Cited by (14) Tweetations (6) Metrics

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  3. Petroff D, Nasir A, Moin K, Loveless B, Moshirfar O, Hoopes P, Moshirfar M. Evaluating the Accuracy of Artificial Intelligence (AI)-Generated Illustrations for Laser-Assisted In Situ Keratomileusis (LASIK), Photorefractive Keratectomy (PRK), and Small Incision Lenticule Extraction (SMILE). Cureus 2024 View
  4. Moin K, Nasir A, Petroff D, Loveless B, Moshirfar O, Hoopes P, Moshirfar M. Assessment of Generative Artificial Intelligence (AI) Models in Creating Medical Illustrations for Various Corneal Transplant Procedures. Cureus 2024 View
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  6. Ogundiya O, Rahman T, Valnarov-Boulter I, Young T. Looking Back on Digital Medical Education Over the Last 25 Years and Looking to the Future: Narrative Review. Journal of Medical Internet Research 2024;26:e60312 View
  7. Safadi M, Zayegh O, Hawoot Z. Advancing Innovation in Medical Presentations: A Guide for Medical Educators to Use Images Generated With Artificial Intelligence. Cureus 2024 View
  8. Gupta N, Khatri K, Malik Y, Lakhani A, Kanwal A, Aggarwal S, Dahuja A. Exploring prospects, hurdles, and road ahead for generative artificial intelligence in orthopedic education and training. BMC Medical Education 2024;24(1) View
  9. Andrew K, Montalbano M. Through a Glass Darkly: Perceptions of Ethnoracial Identity in Artificial Intelligence Generated Medical Vignettes and Images. Medical Science Educator 2025 View
  10. Senft Everson N, Gaysynsky A, Iles I, Schrader K, Chou W. What does an AI-generated “cancer survivor” look like? An analysis of images generated by text-to-image tools. Journal of Cancer Survivorship 2025 View
  11. Phipps B, Hadoux X, Sheng B, Campbell J, Liu T, Keane P, Cheung C, Chung T, Wong T, van Wijngaarden P. AI image generation technology in ophthalmology: Use, misuse and future applications. Progress in Retinal and Eye Research 2025;106:101353 View
  12. Haider S, Prabha S, Gomez-Cabello C, Borna S, Pressman S, Genovese A, Trabilsy M, Galvao A, Aziz K, Murray P, Parte Y, Yu Y, Tao C, Forte A. A Validity Analysis of Text-to-Image Generative Artificial Intelligence Models for Craniofacial Anatomy Illustration. Journal of Clinical Medicine 2025;14(7):2136 View
  13. Soroudi D, Rouhani D, Patel A, Sadjadi R, Behnam-Hanona R, Oleck N, Falade I, Piper M, Hansen S. Dall-E in hand surgery: Exploring the utility of ChatGPT image generation. Surgery Open Science 2025;26:64 View
  14. Bae J, Kim G, Kim H, Han S, Youn K. Comparison of anatomy image generation capability in AI image generation models. Journal of Visual Communication in Medicine 2025:1 View