Two-Pronged Human Evaluation of ChatGPT Self-Correction in Radiology Report Simplification

• URL: http://arxiv.org/abs/2406.18859v1
• Date: Thu, 27 Jun 2024 03:05:35 GMT
• Title: Two-Pronged Human Evaluation of ChatGPT Self-Correction in Radiology Report Simplification
• Authors: Ziyu Yang, Santhosh Cherian, Slobodan Vucetic,
• Abstract summary: This study explores the suitability of large language models in automatically generating those simplifications. We propose a new evaluation protocol that employs radiologists and laypeople, where radiologists verify the factual correctness of simplifications. Our experimental results demonstrate the effectiveness of self-correction prompting in producing high-quality simplifications.
• Score: 5.059120569845976
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Radiology reports are highly technical documents aimed primarily at doctor-doctor communication. There has been an increasing interest in sharing those reports with patients, necessitating providing them patient-friendly simplifications of the original reports. This study explores the suitability of large language models in automatically generating those simplifications. We examine the usefulness of chain-of-thought and self-correction prompting mechanisms in this domain. We also propose a new evaluation protocol that employs radiologists and laypeople, where radiologists verify the factual correctness of simplifications, and laypeople assess simplicity and comprehension. Our experimental results demonstrate the effectiveness of self-correction prompting in producing high-quality simplifications. Our findings illuminate the preferences of radiologists and laypeople regarding text simplification, informing future research on this topic.

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