@Article{info:doi/10.2196/50163,
author="Roster, Katie
and Kann, Rebecca B
and Farabi, Banu
and Gronbeck, Christian
and Brownstone, Nicholas
and Lipner, Shari R",
title="Readability and Health Literacy Scores for ChatGPT-Generated Dermatology Public Education Materials: Cross-Sectional Analysis of Sunscreen and Melanoma Questions",
journal="JMIR Dermatol",
year="2024",
month="Mar",
day="6",
volume="7",
pages="e50163",
keywords="ChatGPT; artificial intelligence; AI; LLM; LLMs; large language model; language model; language models; generative; NLP; natural language processing; health disparities; health literacy; readability; disparities; disparity; dermatology; health information; comprehensible; comprehensibility; understandability; patient education; public education; health education; online information",
issn="2562-0959",
doi="10.2196/50163",
url="https://derma.jmir.org/2024/1/e50163",
url="https://doi.org/10.2196/50163",
url="http://www.ncbi.nlm.nih.gov/pubmed/38446502"
}