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

Xiaoqiang Liu, Yubin Wang, Zicheng Huang, Boming Xu, Yilin Zeng +6 more
2/13/2024
cs.AI

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Abstract

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.

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Cite this paper

@article{liu2024application,
  title  = {The Application of ChatGPT in Responding to Questions Related to the Boston Bowel Preparation Scale},
  author = {Xiaoqiang Liu and Yubin Wang and Zicheng Huang and Boming Xu and Yilin Zeng and Xinqi Chen and Zilong Wang and Enning Yang and Xiaoxuan Lei and Yisen Huang and Xiaobo Liu},
  year   = {2024},
  eprint = {2402.08492},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2402.08492v1}
}

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