Multi-Agent Intelligence for Multidisciplinary Decision-Making in Gastrointestinal Oncology
Abstrak
Multimodal clinical reasoning in the field of gastrointestinal (GI) oncology necessitates the integrated interpretation of endoscopic imagery, radiological data, and biochemical markers. Despite the evident potential exhibited by Multimodal Large Language Models (MLLMs), they frequently encounter challenges such as context dilution and hallucination when confronted with intricate, heterogeneous medical histories. In order to address these limitations, a hierarchical Multi-Agent Framework is proposed, which emulates the collaborative workflow of a human Multidisciplinary Team (MDT). The system attained a composite expert evaluation score of 4.60/5.00, thereby demonstrating a substantial improvement over the monolithic baseline. It is noteworthy that the agent-based architecture yielded the most substantial enhancements in reasoning logic and medical accuracy. The findings indicate that mimetic, agent-based collaboration provides a scalable, interpretable, and clinically robust paradigm for automated decision support in oncology.
Penulis (28)
Rongzhao Zhang
Junqiao Wang
Shuyun Yang
Mouxiao Bian
Chihao Zhang
Dongyang Wang
Qiujuan Yan
Yun Zhong
Yuwei Bai
Guanxu Zhu
Kangkun Mao
Miao Wang
Chao Ding
Renjie Lu
Lei Wang
Lei Zheng
Tao Zheng
Xi Wang
Zhuo Fan
Bing Han
Meiling Liu
Luyi Jiang
Dongming Shan
Wenzhong Jin
Jiwei Yu
Zheng Wang
Jie Xu
Meng Luo
Akses Cepat
- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓