Multi-Agent Intelligence for Multidisciplinary Decision-Making in Gastrointestinal Oncology

Reading time: 2 minute
...

📝 Original Info

  • Title: Multi-Agent Intelligence for Multidisciplinary Decision-Making in Gastrointestinal Oncology
  • ArXiv ID: 2512.08674
  • Date: 2025-12-09
  • Authors: 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

📝 Abstract

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 framework under consideration decomposes diagnostic reasoning into five specialised agents: a Visual-Language Endoscopy Agent for morphological assessment, o...

📄 Full Content

The Multidisciplinary Team (MDT) represents the gold standard in modern oncology, offering a collaborative platform where radiologists, endoscopists, pathologists, and oncologists synthesize diverse data streams to formulate personalized management plans [4]. In the context of gastrointestinal (GI) cancer, this process

…(Content truncated for length.)

📸 Image Gallery

Figure1.png

Reference

This content is AI-processed based on open access ArXiv data.

Start searching

Enter keywords to search articles

↑↓
ESC
⌘K Shortcut