文章 : 

肿瘤学临床决策自主人工智能代理系统的开发与验证

Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology 

原文发布日期: 2025-06-06

英文摘要:

Clinical decision-making in oncology is complex, requiring the integration of multimodal data and multidomain expertise. We developed and evaluated an autonomous clinical artificial intelligence (AI) agent leveraging GPT-4 with multimodal precision oncology tools to support personalized clinical decision-making. The system incorporates vision transformers for detecting microsatellite instability and KRAS and BRAF mutations from histopathology slides, MedSAM for radiological image segmentation and web-based search tools such as OncoKB, PubMed and Google. Evaluated on 20 realistic multimodal patient cases, the AI agent autonomously used appropriate tools with 87.5% accuracy, reached correct clinical conclusions in 91.0% of cases and accurately cited relevant oncology guidelines 75.5% of the time. Compared to GPT-4 alone, the integrated AI agent drastically improved decision-making accuracy from 30.3% to 87.2%. These findings demonstrate that integrating language models with precision oncology and search tools substantially enhances clinical accuracy, establishing a robust foundation for deploying AI-driven personalized oncology support systems.

摘要翻译：

肿瘤学临床决策具有高度复杂性，需要整合多模态数据和跨领域专业知识。我们开发并评估了一款基于GPT-4的自主临床人工智能（AI）系统，通过整合多模态精准肿瘤学工具来支持个性化临床决策。该体系包含：用于从病理切片检测微卫星不稳定状态及KRAS/BRAF基因突变的视觉转换器、医学图像分割模型MedSAM，以及OncoKB知识库、PubMed和Google等网络检索工具。在20例模拟真实场景的多模态患者案例评估中，该AI系统工具调用准确率达87.5%，临床结论正确率为91.0%，肿瘤学指南引用准确率为75.5%。相较于单独使用GPT-4，整合型AI系统将决策准确率从30.3%显著提升至87.2%。研究结果表明，将语言模型与精准肿瘤学工具及检索系统相结合，能大幅提升临床决策精确度，为部署AI驱动的个性化肿瘤诊疗支持系统奠定了坚实基础。

原文链接:

https://www.nature.com/articles/s43018-025-00991-6