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

Generative Language Models Including ChatGPT (320) Chatbots and Conversational Agents (542) Clinical Information and Decision Making (1426) Artificial Intelligence (1409) Natural Language Processing (704) e-Learning and Digital Medical Education (701)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51926, first published .
Uncovering Language Disparity of ChatGPT on Retinal Vascular Disease Classification: Cross-Sectional Study

Uncovering Language Disparity of ChatGPT on Retinal Vascular Disease Classification: Cross-Sectional Study

Uncovering Language Disparity of ChatGPT on Retinal Vascular Disease Classification: Cross-Sectional Study

Authors of this article:

Xiaocong Liu1, 2 Author Orcid Image ;   Jiageng Wu2 Author Orcid Image ;   An Shao1 Author Orcid Image ;   Wenyue Shen1 Author Orcid Image ;   Panpan Ye1 Author Orcid Image ;   Yao Wang1 Author Orcid Image ;   Juan Ye1 Author Orcid Image ;   Kai Jin1 Author Orcid Image ;   Jie Yang2 Author Orcid Image
Article Authors Cited by (19) Tweetations (4) Metrics

Journals

  1. Mishra V, Sarraju A, Kalwani N, Dexter J. Evaluation of Prompts to Simplify Cardiovascular Disease Information Generated Using a Large Language Model: Cross-Sectional Study. Journal of Medical Internet Research 2024;26:e55388 View
  2. Chen X, Zhang W, Xu P, Zhao Z, Zheng Y, Shi D, He M. FFA-GPT: an automated pipeline for fundus fluorescein angiography interpretation and question-answer. npj Digital Medicine 2024;7(1) View
  3. Wu J, Liu X, Li M, Li W, Su Z, Lin S, Garay L, Zhang Z, Zhang Y, Zeng Q, Shen J, Yuan C, Yang J. Clinical Text Datasets for Medical Artificial Intelligence and Large Language Models — A Systematic Review. NEJM AI 2024;1(6) View
  4. Tailor P, D'Souza H, Li H, Starr M. Vision of the future: large language models in ophthalmology. Current Opinion in Ophthalmology 2024;35(5):391 View
  5. Yang Z, Wang D, Zhou F, Song D, Zhang Y, Jiang J, Kong K, Liu X, Qiao Y, Chang R, Han Y, Li F, Tham C, Zhang X. Understanding natural language: Potential application of large language models to ophthalmology. Asia-Pacific Journal of Ophthalmology 2024;13(4):100085 View
  6. Sallam M, Al-Mahzoum K, Alshuaib O, Alhajri H, Alotaibi F, Alkhurainej D, Al-Balwah M, Barakat M, Egger J. Language discrepancies in the performance of generative artificial intelligence models: an examination of infectious disease queries in English and Arabic. BMC Infectious Diseases 2024;24(1) View
  7. Fei X, Tang Y, Zhang J, Zhou Z, Yamamoto I, Zhang Y. Evaluating cognitive performance: Traditional methods vs. ChatGPT. DIGITAL HEALTH 2024;10 View
  8. Sallam M, Al-Mahzoum K, Almutawaa R, Alhashash J, Dashti R, AlSafy D, Almutairi R, Barakat M. The performance of OpenAI ChatGPT-4 and Google Gemini in virology multiple-choice questions: a comparative analysis of English and Arabic responses. BMC Research Notes 2024;17(1) View
  9. Kalaw F, Baxter S. Ethical considerations for large language models in ophthalmology. Current Opinion in Ophthalmology 2024;35(6):438 View
  10. Sallam M, Al-Salahat K, Eid H, Egger J, Puladi B. Human versus Artificial Intelligence: ChatGPT-4 Outperforming Bing, Bard, ChatGPT-3.5 and Humans in Clinical Chemistry Multiple-Choice Questions. Advances in Medical Education and Practice 2024;Volume 15:857 View
  11. Sevgi M, Ruffell E, Antaki F, Chia M, Keane P. Foundation models in ophthalmology: opportunities and challenges. Current Opinion in Ophthalmology 2025;36(1):90 View
  12. Bellanda V, Santos M, Ferraz D, Jorge R, Melo G. Applications of ChatGPT in the diagnosis, management, education, and research of retinal diseases: a scoping review. International Journal of Retina and Vitreous 2024;10(1) View
  13. Sallam M, Elsayed W, Al-Shorbagy M, Barakat M, El Khatib S, Ghach W, Alwan N, Hallit S, Malaeb D. ChatGPT usage and attitudes are driven by perceptions of usefulness, ease of use, risks, and psycho-social impact: a study among university students in the UAE. Frontiers in Education 2024;9 View
  14. Leon M, Ruaengsri C, Pelletier G, Bethencourt D, Shibata M, Flores M, Shudo Y. Harnessing the Power of ChatGPT in Cardiovascular Medicine: Innovations, Challenges, and Future Directions. Journal of Clinical Medicine 2024;13(21):6543 View
  15. Reuben J, Meiri H, Arien-Zakay H. AI’s pivotal impact on redefining stakeholder roles and their interactions in medical education and health care. Frontiers in Digital Health 2024;6 View
  16. Su Z, Jin K, Wu H, Luo Z, Grzybowski A, Ye J. Assessment of Large Language Models in Cataract Care Information Provision: A Quantitative Comparison. Ophthalmology and Therapy 2024 View
  17. Ming S, Yao X, Guo X, Guo Q, Xie K, Chen D, Lei B. Performance of ChatGPT in Ophthalmic Registration and Clinical Diagnosis: Cross-Sectional Study. Journal of Medical Internet Research 2024;26:e60226 View
  18. Ho C, Tian T, Ayers A, Aaron R, Phillips V, Wolf R, Mathioudakis N, Dai T, Klonoff D. Qualitative metrics from the biomedical literature for evaluating large language models in clinical decision-making: a narrative review. BMC Medical Informatics and Decision Making 2024;24(1) View
  19. Ruamviboonsuk P, Arjkongharn N, Vongsa N, Pakaymaskul P, Kaothanthong N. Discriminative, generative artificial intelligence, and foundation models in retina imaging. Taiwan Journal of Ophthalmology 2024 View