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

Vishala Mishra   1 * , MBBS, MMCi ;   Ashish Sarraju   2 , MD ;   Neil M Kalwani   3, 4 , MD, MPP ;   Joseph P Dexter   5, 6, 7 * , PhD

1 Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, United States

2 Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH, United States

3 Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, United States

4 Division of Cardiovascular Medicine and the Cardiovascular Institute, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States

5 Data Science Initiative, Harvard University, Allston, MA, United States

6 Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, United States

7 Institute of Collaborative Innovation, University of Macau, Taipa, Macao

*these authors contributed equally

Corresponding Author:

  • Joseph P Dexter, PhD
  • Data Science Initiative
  • Harvard University
  • Science and Engineering Complex 1.312-10
  • 150 Western Avenue
  • Allston, MA, 02134
  • United States
  • Phone: 1 8023381330
  • Email: jdexter@fas.harvard.edu