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

Research Letter (37) mHealth for Data Collection and Research (955) Chatbots and Conversational Agents (531) Artificial Intelligence (1371) Natural Language Processing (693) Machine Learning (1465) Cardiology (159) Cardiovascular Disease Prevention (138) Generative Language Models Including ChatGPT (311)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55388, first published .
Evaluation of Prompts to Simplify Cardiovascular Disease Information Generated Using a Large Language Model: Cross-Sectional Study

Evaluation of Prompts to Simplify Cardiovascular Disease Information Generated Using a Large Language Model: Cross-Sectional Study

Evaluation of Prompts to Simplify Cardiovascular Disease Information Generated Using a Large Language Model: Cross-Sectional Study

Authors of this article:

Vishala Mishra1 Author Orcid Image ;   Ashish Sarraju2 Author Orcid Image ;   Neil M Kalwani3, 4 Author Orcid Image ;   Joseph P Dexter5, 6, 7 Author Orcid Image
Article Authors Cited by (3) Tweetations (6) Metrics

Journals

  1. Mishra V, Blasi D, Dexter J. Bridging Ethics and Evidence: Language as a Critical Determinant of Health Equity. The American Journal of Bioethics 2024;24(11):66 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. 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