Enhancing the Readability of Online Patient Education Materials Using Large Language Models: Cross-Sectional Study

13 indexed citations
published 2025

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Fields of papers citing Enhancing the Readability of Online Patient Education Materials Using Large Language Models: Cross-Sectional Study

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

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About Enhancing the Readability of Online Patient Education Materials Using Large Language Models: Cross-Sectional Study

This paper, published in 2025, received 13 indexed citations . Written by John Will, Jonah Zaretsky and Paul Testa covering the research area of General Health Professions, Artificial Intelligence and Health. It is primarily cited by scholars working on Health Informatics (6 citations), General Health Professions (4 citations) and Radiology, Nuclear Medicine and Imaging (2 citations). Published in Journal of Medical Internet Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.2196/69955.

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