聊天Endoscopist:一个域特定的聊天机器人,用于胃肠道疾病的图像
Annisa Ristya Rahmanti1,2, Xiaohong W Gao1
1Department of Computer Science, Faculty of Science and Technology, Middlesex University, London, United Kingdom.
Studies in health technology and informatics
|May 17, 2025
概括
一个新的聊天机器人,聊天Endoscopist,被开发用于食道癌症知识. 尽管有专门的培训,但由于有限的微调数据,它在文本准确性和语言多样性方面被ChatGPT所超越.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
背景情况:
- 大型语言模型 (LLM) 需要对特定领域的知识进行增强.
- 食道癌症研究需要专门的信息检索和理解.
研究的目的:
- 开发聊天Endoscopist,一个专门用于食道癌症知识的聊天机器人.
- 为了评估聊天Endoscopist的表现与一般目的的LLM,ChatGPT相比.
- 评估将图像纳入医疗聊天机器人的有用性.
主要方法:
- 微调一个BioMistral LLM与50个医学文献文件.
- 开发聊天Endoscopist具有集成的图像检索功能.
- 使用精度,回忆,F1分数,类型标记比率和词汇密度对聊天Endoscopist和ChatGPT进行比较分析.
主要成果:
- 聊天GPT在精度 (0.210比0.148),回忆 (0.323比0.049) 和F1得分 (0.266比0.099) 方面表现优于聊天Endoscopist.
- 聊天GPT表现出优越的词汇多样性 (TTR:0.772对比0.717) 和词汇密度 (0.813对比0.781).
- 图像检索是功能性的,但主要用于查询阐明.
结论:
- 有限的微调数据可能影响了聊天Endoscopist的专业准确性.
- 需要进一步的研究,以平衡医学LLM的领域特定准确性和语言灵活性.
- 整合图像显示出潜力,但需要进一步开发以获得最佳影响.
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