医学 AI

Causal Learning in Biomedical Applications: Krebs Cycle as a Benchmark

生物医学应用中的因果学习：柠檬酸循环作为基准

Xiaoyu He, Petr Ryšavý, Jakub Mareček

机构 * AI Center（人工智能中心） ； Department of Computer Science（计算机科学系） ； Czech Technical University in Prague（布拉格捷克技术大学） 纠错

专题命中 医学数据与评测 ：biomedical(title)；分类 cs.LG

AI总结 本文提出基于柠檬酸循环模拟的新基准数据集，用于评估因果发现方法在时间序列数据上的性能，包含真实因果图和多种评估指标。

CRIMSON: A Clinically-Grounded LLM-Based Metric for Generative Radiology Report Evaluation

CRIMSON：一种基于临床的LLM评估指标用于生成放射学报告评估

Mohammed Baharoon, Thibault Heintz, Siavash Raissi, Mahmoud Alabbad, Mona Alhammad, Hassan AlOmaish, Sung Eun Kim, Oishi Banerjee, Pranav Rajpurkar

机构 * Department of Biomedical Informatics, Harvard Medical School（生物医学信息学系，哈佛医学院） ； Department of Radiation Oncology, Mass General Brigham（放射肿瘤科，麻省总医院与布里奇沃特医院） ； King Fahad Hospital, Al-Ahsa Health Cluster, Al Hofuf, Saudi Arabia（国王法赫德医院，阿尔阿萨卫生集群，阿尔霍夫，沙特阿拉伯） ； Ras-Tanura General Hospital, Ministry of Health, Eastern Province, Saudi Arabia（拉斯-坦纳医院，卫生部，东部省，沙特阿拉伯） ； Department of Medical Imaging, King Abdulaziz Medical City, Ministry of National Guard, Riyadh, Saudi Arabia（医学影像科，国王阿卜杜勒-阿齐兹医疗城，国民卫队部，利雅得，沙特阿拉伯） 纠错

专题命中 医学数据与评测 ：radiology(title)；分类 cs.CV

AI总结 CRIMSON是一种基于临床的LLM评估指标，用于评估生成的放射学报告，通过考虑诊断正确性、上下文相关性和患者安全，提供更全面的评估方法。

Personalized Federated Learning with Residual Fisher Information for Medical Image Segmentation

具有残差信息鱼尔矩阵的个性化联邦学习用于医学图像分割

Meilu Zhu, Yuxing Li, Zhiwei Wang, Edmund Y. Lam

机构 * Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China（电子与电气工程系，香港大学，香港，中国） 纠错

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV

AI总结 本文提出pFL-ResFIM框架，通过残差信息鱼尔矩阵量化模型参数对领域差异的敏感性，实现客户端自适应个性化，在公共数据集上验证了其有效性。

Comments accepted by ISBI 2026

Hierarchical Dual-Strategy Unlearning for Biomedical and Healthcare Intelligence Using Imperfect and Privacy-Sensitive Medical Data

层次化双策略去学习用于生物医学与医疗智能的不完美和隐私敏感医疗数据

Yi Zhang, Chao Zhang, Zijian Li, Tianxiang Xu, Kunyu Zhang, Zhan Gao, Meinuo Li, Xiaohan Zhang, Qichao Qi, Bing Chen

机构 * Department of Neurosurgery, Qilu Hospital of Shandong University and Institute of Brain and Brain-Inspired Science（齐鲁医院山东大学神经外科和脑科学与脑启发科学研究院） ； Department of Neurosurgery, The Affiliated Hospital of Qingdao University（青岛大学附属医院神经外科） ； Department of Neurosurgery, Peking Union Medical College Hospital（北京地坛医院神经外科） ； School of Software and Microelectronics, Peking University（北京大学软件与微电子学院） ； College of Artificial Intelligence, Dalian Maritime University（大连海事大学人工智能学院） ； University of Colorado Boulder（科罗拉多大学波尔德分校） ； Zhengzhou University（郑州大学） ； The University of Hong Kong（香港大学） ； Georgia Institute of Technology（佐治亚理工学院） 纠错

专题命中 医学数据与评测 ：biomedical(title)；分类 cs.LG

AI总结 本文提出层次化双策略去学习框架，用于在医疗数据中精确移除专业性知识并保留基本医疗能力，同时保障隐私并满足合规要求。

Democratising Clinical AI through Dataset Condensation for Classical Clinical Models

通过数据集压缩实现临床AI的民主化

Anshul Thakur, Soheila Molaei, Pafue Christy Nganjimi, Joshua Fieggen, Andrew A. S. Soltan, Danielle Belgrave, Lei Clifton, David A. Clifton

专题命中 医学数据与评测 ：clinical AI(title)；分类 cs.LG

AI总结 本文提出了一种基于差分隐私的零阶优化框架，通过数据集压缩实现临床模型的数据共享，同时保障患者隐私。

Comments 22 pages, 5 figures, 5 tables

A labeled dataset of simulated phlebotomy procedures for medical AI: polygon annotations for object detection and human-object interaction

带有标注的模拟采血程序数据集用于医疗AI：用于目标检测和人-物交互的多边形标注

Raúl Jiménez Cruz, César Torres-Huitzil, Marco Franceschetti, Ronny Seiger, Luciano García-Bañuelos, Barbara Weber

机构 * Institute of Computer Science（计算机科学研究所） ； University of St.Gallen（圣加伦大学） 纠错

专题命中 医学数据与评测 ：medical AI(title)；分类 cs.CV

AI总结 本文提出一个包含11884张标注图像的数据集，用于医疗AI中的目标检测和人-物交互研究，支持医疗培训自动化和教育系统开发。

A Reproducible Framework for Bias-Resistant Machine Learning on Small-Sample Neuroimaging Data

一种可重复的偏见抵御小样本神经影像机器学习框架

Jagan Mohan Reddy Dwarampudi, Jennifer L Purks, Joshua Wong, Renjie Hu, Tania Banerjee

机构 * Department of Electrical and Computer Engineering, University of Houston（电子与计算机工程系，休斯顿大学） ； Department of Information Science Technology, University of Houston（信息科学与技术系，休斯顿大学） ； Department of Neurology, College of Medicine, University of Florida（神经病学系，医学院，佛罗里达大学） 纠错

专题命中 医学数据与评测 ：MRI(abstract)；biomedical(abstract)；分类 cs.CV、cs.LG、q-bio

AI总结 本文提出了一种可重复且偏见抵御的机器学习框架，用于小样本神经影像数据，通过领域指导的特征工程、嵌套交叉验证和校准决策阈值优化，提高了模型的可解释性和泛化能力。

Comments Accepted to ISBI 2026, 5 pages with 1 figure

SANEval: Open-Vocabulary Compositional Benchmarks with Failure-mode Diagnosis

SANEval: 开放词汇组合评估基准与失败模式诊断

Rishav Pramanik, Ian E. Nielsen, Jeff Smith, Saurav Pandit, Ravi P. Ramachandran, Zhaozheng Yin

机构 * Stony Brook University（石溪大学） ； nd Set AI Corp.（第二集AI公司） ； Rowan University（罗文大学） 纠错

专题命中 医学数据与评测 ：diagnosis(title)；分类 cs.CV

AI总结 SANEval提出一种开放词汇组合评估基准，结合大型语言模型和增强对象检测器，通过实验展示其在属性绑定、空间关系和数值任务上的评估效果优于现有基准。

Metric Hub: A metric library and practical selection workflow for use-case-driven data quality assessment in medical AI

Metric Hub: 一个用于医疗AI中以用例为导向的数据质量评估的度量库和实用选择流程

Katinka Becker, Maximilian P. Oppelt, Tobias S. Zech, Martin Seyferth, Sandie Cabon, Vanja Miskovic, Ivan Cimrak, Michal Kozubek, Giuseppe D'Avenio, Ilaria Campioni, Jana Fehr, Kanjar De, Ismail Mahmoudi, Emilio Dolgener Cantu, Laurenz Ottmann, Andreas Klaß, Galaad Altares, Jackie Ma, Alireza Salehi M., Nadine R. Lang-Richter, Tobias Schaeffter, Daniel Schwabe

专题命中 医学数据与评测 ：medical AI(title)；分类 cs.LG

AI总结 Metric Hub提出一个医疗AI中以用例为导向的数据质量评估度量库和选择流程，通过度量卡片和决策树提升数据质量评估的实用性与可信度。

PANDA-PLUS-Bench: A Clinical Benchmark for Evaluating Robustness of AI Foundation Models in Prostate Cancer Diagnosis

PANDA-PLUS-Bench：用于评估前列腺癌诊断中AI基础模型鲁棒性的临床基准

Joshua L. Ebbert, Dennis Della Corte

专题命中 医学数据与评测 ：diagnosis(title)；分类 cs.CV

AI总结 PANDA-PLUS-Bench通过定制基准数据集评估AI基础模型在前列腺癌Gleason分级中的鲁棒性，揭示模型在生物特征捕获和跨滑片准确率上的差异。

Comments 21 pages, 5 figures, 6 Tables

Privacy-Preserving Federated Vision Transformer Learning Leveraging Lightweight Homomorphic Encryption in Medical AI

利用轻量级同态加密实现隐私保护的联邦视觉变换器学习用于医疗AI

Al Amin, Kamrul Hasan, Liang Hong, Sharif Ullah

机构 * Department of Electrical and Computer Engineering, Tennessee State University（电气与计算机工程系，田纳西州立大学） ； University of Central Arkansas（中央阿肯色大学） 纠错

专题命中 医学数据与评测 ：medical AI(title)；分类 cs.CV

AI总结 本文提出一种结合视觉变换器与轻量级同态加密的隐私保护联邦学习框架，通过加密CLS标记实现医疗AI中的安全多机构病理学分类，显著降低通信开销并增强隐私保护。

Comments 7 pages, 4 figures

Journal ref IEEE ICNC2026

Adversarially-Aware Architecture Design for Robust Medical AI Systems

Alyssa Gerhart, Balaji Iyangar

机构 * Department of Computer Science Benedict College Columbia, SC, USA（计算机科学系 奥本大学 奥斯本, 南卡罗来纳州, 美国） 纠错

专题命中 医学数据与评测 ：medical AI(title)；分类 cs.LG

FedFiTS: Fitness-Selected, Slotted Client Scheduling for Trustworthy Federated Learning in Healthcare AI

Ferdinand Kahenga, Antoine Bagula, Sajal K. Das, Patrick Sello

机构 * Department of Computer Science University of the Western Cape（计算机科学系，西开普敦大学） ； Department of Computer Science Missouri University of Science and Technology（计算机科学系，密苏里科学与技术大学） 纠错

专题命中 医学数据与评测 ：healthcare AI(title)；分类 cs.LG

Deep Modeling and Optimization of Medical Image Classification

Yihang Wu, Muhammad Owais, Reem Kateb, Ahmad Chaddad

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV

Comments Accepted in ISBI2025

Building a Human-Verified Clinical Reasoning Dataset via a Human LLM Hybrid Pipeline for Trustworthy Medical AI

Chao Ding, Mouxiao Bian, Pengcheng Chen, Hongliang Zhang, Tianbin Li, Lihao Liu, Jiayuan Chen, Zhuoran Li, Yabei Zhong, Yongqi Liu, Haiqing Huang, Dongming Shan, Junjun He, Jie Xu

机构 * Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） ； Shanghai Jiao Tong University（上海交通大学） ； Shanghai Kupas Technology Limited Company（上海库帕斯科技有限公司） 纠错

专题命中 医学数据与评测 ：medical AI(title)；分类 cs.CV

Shape Modeling of Longitudinal Medical Images: From Diffeomorphic Metric Mapping to Deep Learning

Edwin Tay, Nazli Tümer, Amir A. Zadpoor

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV

Is fitting error a reliable metric for assessing deformable motion correction in quantitative MRI?

Fanwen Wang, Ke Wen, Yaqing Luo, Yinzhe Wu, Jiahao Huang, Dudley J. Pennell, Pedro F. Ferreira, Andrew D. Scott, Sonia Nielles-Vallespin, Guang Yang

专题命中 医学数据与评测 ：MRI(title)；分类 eess.IV

Comments 5 pages, 5 figures. Accepted by ISBI 2025

LNQ 2023 challenge: Benchmark of weakly-supervised techniques for mediastinal lymph node quantification

Reuben Dorent, Roya Khajavi, Tagwa Idris, Erik Ziegler, Bhanusupriya Somarouthu, Heather Jacene, Ann LaCasce, Jonathan Deissler, Jan Ehrhardt, Sofija Engelson, Stefan M. Fischer, Yun Gu, Heinz Handels, Satoshi Kasai, Satoshi Kondo, Klaus Maier-Hein, Julia A. Schnabel, Guotai Wang, Litingyu Wang, Tassilo Wald, Guang-Zhong Yang, Hanxiao Zhang, Minghui Zhang, Steve Pieper, Gordon Harris, Ron Kikinis, Tina Kapur

专题命中 医学数据与评测 ：medical image(abstract)；CT(abstract)；biomedical(comments,journal_ref)；分类 cs.CV

Comments Submitted to MELBA; Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2025:001

Journal ref Machine.Learning.for.Biomedical.Imaging. 3 (2025)

FedDAG: Federated Domain Adversarial Generation Towards Generalizable Medical Image Analysis

Haoxuan Che, Yifei Wu, Haibo Jin, Yong Xia, Hao Chen

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV

Empowering Agricultural Insights: RiceLeafBD -- A Novel Dataset and Optimal Model Selection for Rice Leaf Disease Diagnosis through Transfer Learning Technique

Sadia Afrin Rimi, Md. Jalal Uddin Chowdhury, Rifat Abdullah, Iftekhar Ahmed, Mahrima Akter Mim, Mohammad Shoaib Rahman

专题命中 医学数据与评测 ：diagnosis(title)；分类 cs.CV

FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysis

Guochen Yan, Luyuan Xie, Xinyi Gao, Wentao Zhang, Qingni Shen, Yuejian Fang, Zhonghai Wu

专题命中 医学数据与评测 ：medical image(title)；分类 cs.LG

Comments Accepted by AAAI 2025

Non-parametric regularization for class imbalance federated medical image classification

Jeffry Wicaksana, Zengqiang Yan, Kwang-Ting Cheng

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV

Comments arXiv admin note: text overlap with arXiv:2305.00738

MH-pFLGB: Model Heterogeneous personalized Federated Learning via Global Bypass for Medical Image Analysis

Luyuan Xie, Manqing Lin, ChenMing Xu, Tianyu Luan, Zhipeng Zeng, Wenjun Qian, Cong Li, Yuejian Fang, Qingni Shen, Zhonghai Wu

专题命中 医学数据与评测 ：medical image(title)；分类 cs.LG

Comments arXiv admin note: text overlap with arXiv:2405.06822

Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model

Salman Rahman, Lavender Yao Jiang, Saadia Gabriel, Yindalon Aphinyanaphongs, Eric Karl Oermann, Rumi Chunara

专题命中 医学数据与评测 ：healthcare AI(title)；分类 cs.LG

Enhancing Robustness in Biomedical NLI Models: A Probing Approach for Clinical Trials

Ata Mustafa

专题命中 医学数据与评测 ：biomedical(title)；分类 cs.LG

NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies

Atif Khan, Conor Lawless, Amy Vincent, Charlotte Warren, Valeria Di Leo, Tiago Gomes, A. Stephen McGough

专题命中 医学数据与评测 ：pathology(abstract)；biomedical(abstract)；分类 cs.CV、cs.LG、q-bio

Comments Paper accepted at the Big Data Analytics for Health and Medicine (BDA4HM) workshop, IEEE BigData 2023, December 15th-18th, 2023, Sorrento, Italy, 07 pages. arXiv admin note: substantial text overlap with arXiv:2311.11099

Introducing NCL-SM: A Fully Annotated Dataset of Images from Human Skeletal Muscle Biopsies

Atif Khan, Conor Lawless, Amy Vincent, Charlotte Warren, Valeria Di Leo, Tiago Gomes, A. Stephen McGough

专题命中 医学数据与评测 ：pathology(abstract)；biomedical(abstract)；分类 cs.CV、cs.LG、q-bio

Comments Extended Abstract presented at Machine Learning for Health (ML4H) symposium 2023, December 10th, 2023, New Orleans, United States, 09 pages Full Paper presented at Big Data Analytics for Health and Medicine (BDA4HM) workshop, IEEE BigData 2023, December 15th-18th, 2023, Sorrento, Italy

CMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction

Chengyan Wang, Jun Lyu, Shuo Wang, Chen Qin, Kunyuan Guo, Xinyu Zhang, Xiaotong Yu, Yan Li, Fanwen Wang, Jianhua Jin, Zhang Shi, Ziqiang Xu, Yapeng Tian, Sha Hua, Zhensen Chen, Meng Liu, Mengting Sun, Xutong Kuang, Kang Wang, Haoran Wang, Hao Li, Yinghua Chu, Guang Yang, Wenjia Bai, Xiahai Zhuang, He Wang, Jing Qin, Xiaobo Qu

专题命中 医学数据与评测 ：MRI(title)；分类 cs.CV

Comments 14 pages, 8 figures

Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis

Shigehiko Schamoni, Michael Hagmann, Stefan Riezler

专题命中 医学数据与评测 ：diagnosis(title)；分类 cs.LG

Comments Accepted at MLHC 2022

Journal ref Proceedings of the 7th Machine Learning for Healthcare Conference, PMLR 182:123-145, 2022

FCA: Taming Long-tailed Federated Medical Image Classification by Classifier Anchoring

Jeffry Wicaksana, Zengqiang Yan, Kwang-Ting Cheng

专题命中 医学数据与评测 ：medical image(title)；分类 cs.CV

Comments submitted for publication