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简化前列腺癌病理学报告的大型语言模型的比较评估:ChatGPT和Gemini
Haoyang Zeng1,2, Yangguang Yuan1, Xiang Wu3
1Department of Radiology, The Third Affiliated Hospital of Shenzhen University (Luohu People's Hospital), Shenzhen, China.
International journal of surgery (London, England)
|February 3, 2026
概括
像ChatGPT和Gemini这样的大型语言模型 (LLM) 可以简化前列腺癌病理学报告,GPT-4o和Gemini分别在准确性和可理解性方面表现出特殊优势. 这些人工智能工具有望改善患者的理解和临床沟通.
科学领域:
- 人工智能的人工智能
- 医疗信息学 医疗信息学
- 在瘤学瘤学.
背景情况:
- 前列腺癌的病理学报告对患者和临床医生来说可能是复杂的.
- 简化这些报告对于改善理解和沟通至关重要.
研究的目的:
- 评估大型语言模型 (LLM) 包括ChatGPT版本 (GPT-3.5,GPT-4.0,GPT-4o) 和Gemini在简化前列腺癌病理报告中的有效性.
- 通过不同的评估指标来比较这些LLM的表现.
主要方法:
- 一项涉及228名前列腺癌病理学报告的回顾性研究来自两个机构.
- 使用四个LLM (GPT-3.5,GPT-4.0,GPT-4o,Gemini) 来生成简化的文本.
- 用人类评分 (患者,临床医生,病理学家),可读性评分和基于BERT的语义相似性来评估输出.
主要成果:
- 根据病理学家的说法,GPT-4o (Few-Shot) 在准确性和全面性方面表现出色.
- 双子座表现出卓越的可理解性.
- 在所有测试模型中,患者和临床医生的可理解性评级都很高.
- GPT-4o (Few-Shot) 取得了最好的整体阅读等级水平分数.
结论:
- 在简化报告方面,LLM采用不同的策略,平衡简化与结构完整性.
- 这些人工智能工具有可能提高患者的理解和瘤学中的临床沟通.
- 建议进一步对特定领域进行微调,以确保LLMs的安全可靠的临床整合.
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