医学 AI

Vision Language Models versus Machine Learning Models Performance on Polyp Detection and Classification in Colonoscopy Images

视觉语言模型与机器学习模型在结肠镜图像息肉检测与分类中的性能对比

Mohammad Amin Khalafi, Seyed Amir Ahmad Safavi-Naini, Ameneh Salehi, Nariman Naderi, Dorsa Alijanzadeh, Pardis Ketabi Moghadam, Kaveh Kavosi, Negar Golestani, Shabnam Shahrokh, Soltanali Fallah, Jamil S Samaan, Nicholas P. Tatonetti, Nicholas Hoerter, Girish Nadkarni, Hamid Asadzadeh Aghdaei, Ali Soroush

专题命中 诊断辅助 ：pathology(abstract)；diagnosis(abstract)；分类 cs.CV、eess.IV

AI总结 本文对比了视觉语言模型与传统机器学习模型在结肠镜图像息肉检测和分类任务中的性能，发现ResNet50在检测任务中表现最佳，而BiomedCLIP和GPT-4在特定情况下也表现出色。

Comments Code is available at: https://github.com/aminkhalafi/CML-vs-LLM-on-Polyp-Detection. CoI: AlSo serves on the advisory board and holds equity in Virgo Surgical Solutions. The other authors declare no conflicts of interest. Data

Journal ref Scientific Reports 15, 45484 (2025)

LungCURE: Benchmarking Multimodal Real-World Clinical Reasoning for Precision Lung Cancer Diagnosis and Treatment

LungCURE：多模态真实世界临床推理基准测试用于精准肺癌诊断与治疗

Fangyu Hao, Jiayu Yang, Yifan Zhu, Zijun Yu, Qicen Wu, Wang Yunlong, Jiawei Li, Yulin Liu, Xu Zeng, Guanting Chen, Shihao Li, Zhonghong Ou, Meina Song, Mengyang Sun, Haoran Luo, Yu Shi, Yingyi Wang

专题命中 诊断辅助 ：diagnosis(title)

AI总结 本文提出LungCURE基准测试，通过1000个真实世界病例评估多模态模型在肺癌TNM分期、治疗推荐和临床决策支持中的性能，并引入LCAgent框架提升模型在复杂医疗场景中的推理能力。

Comments 20 pages, 22 figures

FedIFL: A federated cross-domain diagnostic framework for motor-driven systems with inconsistent fault modes

FedIFL: 一种用于具有不一致故障模式的电机驱动系统的联邦跨域诊断框架

Zexiao Wang, Yankai Wang, Xiaoqiang Liao, Xinguo Ming, Weiming Shen

专题命中 诊断辅助 ：diagnosis(abstract)；分类 cs.LG

AI总结 针对工业数据稀缺导致的故障诊断模型训练困难，FedIFL通过联邦学习实现隐私保护下的协同训练，通过原型对比学习和特征解耦机制解决跨域标签空间不一致问题，提升全局模型的泛化能力。

Comments The paper is being withdrawn as we found that it did not fully articulate the representation of deep implicit features, which is the core focus of our work. Additionally, the experiments were incomplete and lacked sufficient analysis. We plan to revise the paper, clarify these aspects, and enhance the experimental validation before resubmitting

Let the Agent Steer: Closed-Loop Ranking Optimization via Influence Exchange

让代理引导：通过影响交换实现闭环排名优化

Yin Cheng, Liao Zhou, Xiyu Liang, Dihao Luo, Tewei Lee, Kailun Zheng, Weiwei Zhang, Mingchen Cai, Jian Dong, Andy Zhang

机构 * Shopee 纠错

专题命中 诊断辅助 ：diagnosis(abstract)

AI总结 本文提出Sortify，首个自主LLM驱动的排名优化代理，通过影响交换闭环实现从诊断到参数部署的自动化优化，解决了结构问题并提升了GMV和广告收入。

Automotive Engineering-Centric Agentic AI Workflow Framework

以汽车工程为中心的代理式人工智能工作流框架

Tong Duy Son, Zhihao Liu, Piero Brigida, Yerlan Akhmetov, Gurudevan Devarajan, Kai Liu, Ajinkya Bhave

专题命中 诊断辅助 ：diagnosis(abstract)

AI总结 本文提出Agentic Engineering Intelligence (AEI)框架，通过建模工程工作流为约束性序列决策过程，将设计优化、模拟诊断等任务整合为统一流程，展示如何在汽车工程中实现多样化工作流的统一表达。