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

Theme Issue (2023): Generative & Multimodal AI in Digital Cardiovascular Medicine (6) Machine Learning (1501) Chatbots and Conversational Agents (543) Generative Language Models Including ChatGPT (325) Cardiovascular Medical Education and Training for Health Professionals (5) Cardiology (164) Patient Education in Cardiology (32) Gastroenterology and Hepatology (72) Neurology and Neurosciences (192)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53421, first published .
A Multidisciplinary Assessment of ChatGPT’s Knowledge of Amyloidosis: Observational Study

A Multidisciplinary Assessment of ChatGPT’s Knowledge of Amyloidosis: Observational Study

A Multidisciplinary Assessment of ChatGPT’s Knowledge of Amyloidosis: Observational Study

Authors of this article:

Ryan C King1 Author Orcid Image ;   Jamil S Samaan2 Author Orcid Image ;   Yee Hui Yeo2 Author Orcid Image ;   Yuxin Peng3 Author Orcid Image ;   David C Kunkel4 Author Orcid Image ;   Ali A Habib5 Author Orcid Image ;   Roxana Ghashghaei1 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. McBee J, Han D, Liu L, Ma L, Adjeroh D, Xu D, Hu G. Assessing ChatGPT’s Competency in Addressing Interdisciplinary Inquiries on Chatbot Uses in Sports Rehabilitation: Simulation Study. JMIR Medical Education 2024;10:e51157 View
  2. Aydin S, Karabacak M, Vlachos V, Margetis K. Large language models in patient education: a scoping review of applications in medicine. Frontiers in Medicine 2024;11 View
  3. Ulug E, Gunesli I, Acıkgoz Pinar A, Yildiz B. Evaluating reliability, quality, and readability of ChatGPT's nutritional recommendations for women with polycystic ovary syndrome. Nutrition Research 2025;133:46 View