Can artificial intelligence create human touch in medical writing? A pilot study.

AIM: To assess whether ChatGPT can autonomously generate and select "human touch" elements (anecdotes, beliefs, and old sayings) and produce writing comparable to human-authored manuscripts. METHODS: A disagreement letter was composed and then tasked ChatGPT-5 with writing a new disagreement letter. The model was instructed to select suitable anecdotes from a candidate list and generate new ones. Both letters were compared. Eight experienced researchers independently assessed whether the letters were appealing. RESULTS: ChatGPT was able to select appropriate elements from the candidate list and, importantly, generate new ones. The human-generated letter was found to be more appealing by five of eight reviewers, and the ChatGPT-generated letter by three reviewers. None of the researchers reported that they found the use of human touch inappropriate or disruptive. Conclusion Although a single case was studied, these findings may help inform reflection on the use of LLMs in medical writing.

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PubMed
Published
2026-04-30
Primary Topic
Artificial Intelligence in Healthcare and Education
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article
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article

Can artificial intelligence create human touch in medical writing? A pilot study.

Shigeki Matsubara
PubMed
Artificial Intelligence in Healthcare and Education
article

Can artificial intelligence create human touch in medical writing? A pilot study.

Shigeki Matsubara
article en

Abstract

AIM: To assess whether ChatGPT can autonomously generate and select "human touch" elements (anecdotes, beliefs, and old sayings) and produce writing comparable to human-authored manuscripts. METHODS: A disagreement letter was composed and then tasked ChatGPT-5 with writing a new disagreement letter. The model was instructed to select suitable anecdotes from a candidate list and generate new ones. Both letters were compared. Eight experienced researchers independently assessed whether the letters were appealing. RESULTS: ChatGPT was able to select appropriate elements from the candidate list and, importantly, generate new ones. The human-generated letter was found to be more appealing by five of eight reviewers, and the ChatGPT-generated letter by three reviewers. None of the researchers reported that they found the use of human touch inappropriate or disruptive. Conclusion Although a single case was studied, these findings may help inform reflection on the use of LLMs in medical writing.

PubMedVol. 67(2)
Jichi Medical University (JP)
Quality Education
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare and Education
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