mlsanityData to 7 Oct 2026

The Application of ChatGPT in Responding to Questions Related to the Boston Bowel Preparation Scale

arXiv 2402.08492 ↗First posted 13 Feb 2024cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Background: Colonoscopy, a crucial diagnostic tool in gastroenterology, depends heavily on superior bowel preparation. ChatGPT, a large language model with emergent intelligence which also exhibits potential in medical applications. This study aims to assess the accuracy and consistency of ChatGPT in using the Boston Bowel Preparation Scale (BBPS) for colonoscopy assessment. Methods: We retrospectively collected 233 colonoscopy images from 2020 to 2023. These images were evaluated using the BBPS by 3 senior endoscopists and 3 novice endoscopists. Additionally, ChatGPT also assessed these images, having been divided into three groups and undergone specific Fine-tuning. Consistency was evaluated through two rounds of testing. Results: In the initial round, ChatGPT's accuracy varied between 48.93% and 62.66%, trailing the endoscopists' accuracy of 76.68% to 77.83%. Kappa values for ChatGPT was between 0.52 and 0.53, compared to 0.75 to 0.87 for the endoscopists. Conclusion: While ChatGPT shows promise in bowel preparation scoring, it currently does not match the accuracy and consistency of experienced endoscopists. Future research should focus on in-depth Fine-tuning.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 1 of its 18 references that are in the map. First posted on arXiv 13 Feb 2024.

Builds on

1 of 18 references.

References · 1

  1. 2023Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potentialcited by 39

Built on by

Not cited yet.