Readability and Health Literacy Scores for ChatGPT-Generated Dermatology Public Education Materials: Cross-Sectional Analysis of Sunscreen and Melanoma Questions.
作者信息
Roster Katie, Kann Rebecca B, Farabi Banu, Gronbeck Christian, Brownstone Nicholas, Lipner Shari R
机构信息
New York Medical College, New York, NY, United States.
Dermatology Department, NYC Health + Hospital/Metropolitan, New York, NY, United States.
出版信息
JMIR Dermatol. 2024 Mar 6;7:e50163. doi: 10.2196/50163.
DOI:10.2196/50163
PMID:38446502
Abstract
摘要
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本文引用的文献
[1]
The Use of Large Language Models to Generate Education Materials about Uveitis.
Ophthalmol Retina. 2024-2
[2]
Using ChatGPT for Writing Articles for Patients' Education for Dermatological Diseases: A Pilot Study.
Indian Dermatol Online J. 2023-6-28
[3]
Assessment of internet sources on subungual melanoma.
Melanoma Res. 2020-8
[4]
[5]
Illiteracy among Medicaid recipients and its relationship to health care costs.
J Health Care Poor Underserved. 1994