Medical Text Rewriting for Non-Experts: A Guideline-Driven LLM Approach

Abstract

Medical research is highly specialized, making it difficult for patients and general readers to understand recent findings.Traditionally, text simplification, replacing technical terms with more accessible expressions, has been employed. However, this approach alone is limited in addressing a lack of background knowledge and often results in the loss of important information.Therefore, this study defines “rewriting for non-experts” as a rewriting process that, in addition to simplification, supplements essential background knowledge such as the significance of the research and reasons it is needed and proposes a method for implementing this process using large language models (LLMs).To verify the effectiveness of the proposed approach, a quantitative evaluation using automatic metrics was conducted. The results showed that the method combining the guidelines for human text creation with few-shot examples of reference texts achieved the highest scores.The expansion of the guidelines is planned as part of future work to enable the rewriting of scientific and technological information in a form that is accessible to a broader audience.

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