arXivDaily arXiv每日学术速递 周一至周五更新

科学与医疗

医学 AI

医学智能、临床 AI、医学影像、病理、诊断和医疗健康大模型。

2026-01-27 至 2026-01-27 共收录 10 信号源:cs.CV, cs.LG, q-bio, eess.IV, eess.SP

1. 诊断辅助 10 篇

2601.18556 2026-01-27 cs.CV cs.LG 90%

Generative Diffusion Augmentation with Quantum-Enhanced Discrimination for Medical Image Diagnosis

生成扩散增强与量子增强判别用于医学图像诊断

Jingsong Xia, Siqi Wang

专题命中 诊断辅助 :medical image(title,abstract);diagnosis(title);medical AI(abstract);biomedical(abstract)

AI总结 SDA-QEC通过生成扩散增强与量子增强判别技术,提升医学图像分类的诊断准确性与平衡性能。

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2601.15530 2026-01-27 cs.LG q-bio.NC q-bio.QM 88%

Machine learning-enhanced non-amnestic Alzheimer's disease diagnosis from MRI and clinical features

基于机器学习的非遗忘性阿尔茨海默病从MRI和临床特征诊断

Megan A. Witherow, Michael L. Evans, Ahmed Temtam, Hamid R. Okhravi, Khan M. Iftekharuddin

专题命中 诊断辅助 :MRI(title,abstract);diagnosis(title,abstract);分类 cs.LG、q-bio

AI总结 本文提出基于机器学习的方法,利用MRI和临床数据区分非典型阿尔茨海默病与非AD认知障碍,提高诊断准确率。

Comments 10 pages, 4 figures, 4 tables

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2601.17032 2026-01-27 cs.CV cs.LG 81%

Diagnosis Support of Sickle Cell Anemia by Classifying Red Blood Cell Shape in Peripheral Blood Images

通过分类外周血图像中的红细胞形状支持镰状细胞贫血诊断

Wilkie Delgado-Font, Miriela Escobedo-Nicot, Manuel González-Hidalgo, Silena Herold-Garcia, Antoni Jaume-i-Capó, Arnau Mir

机构 * Facultad de Ciencias Naturales y Exactas, Universidad de Oriente(自然科学与精确科学系,奥里ente大学) Balearic Islands Health Research Institute (IdISBa)(巴利阿里群岛健康研究 institutes(IdISBa)) Department of Mathematics and Computer Science, Universitat de les Illes Balears(数学与计算机科学系,巴利阿里群岛大学) Research Institute of Health Sciences (IUNICS)(健康科学研究院(IUNICS)) Computational biology and bioinformatics (BIOCOM) Research Group(计算生物学和生物信息学(BIOCOM)研究组)

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

AI总结 本文提出了一种基于外周血图像分析的自动化方法,通过分类红细胞形状来支持镰状细胞贫血的诊断。

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2601.17767 2026-01-27 cs.AI cs.LG 79%

HyCARD-Net: A Synergistic Hybrid Intelligence Framework for Cardiovascular Disease Diagnosis

HyCARD-Net: 一种用于心血管疾病诊断的协同混合智能框架

Rajan Das Gupta, Xiaobin Wu, Xun Liu, Jiaqi He

机构 * Faculty of Information Science and Technology(信息科学与技术学院) American International University–Bangladesh(美国国际大学-孟加拉国) School of Automotive Engineering(汽车工程学院) Chengdu Industry and Trade College(成都行业贸易学院) Faculty of Education(教育学院) Shinawatra University(辛纳瓦特大学) Tilburg School of Social and Behavioral Sciences(蒂尔堡社会与行为科学学院) Tilburg University(蒂尔堡大学)

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

AI总结 HyCARD-Net通过结合深度学习与传统机器学习算法,提出一种混合智能框架,有效提升心血管疾病诊断的准确率和效率,支持联合国可持续发展目标3。

Comments Accepted and published in the 2025 4th International Conference on Image Processing, Computer Vision and Machine Learning (ICICML)

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2601.17977 2026-01-27 cs.CV 76%

Domain-Expert-Guided Hybrid Mixture-of-Experts for Medical AI: Integrating Data-Driven Learning with Clinical Priors

领域专家引导的混合专家模型用于医疗AI:整合数据驱动学习与临床先验

Jinchen Gu, Nan Zhao, Lei Qiu, Lu Zhang

机构 * Department of Computer Science, Indiana University Indianapolis(印第安纳大学印第安纳波利斯分校计算机科学系)

专题命中 诊断辅助 :medical AI(title);分类 cs.CV;biomedical(comments)

AI总结 本文提出DKGH-MoE模型,结合数据驱动学习与临床先验,提升医疗AI的性能和可解释性。

Comments 4 pages; 3 figures; accepted by International Symposium on Biomedical Imaging (ISBI) 2026

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2509.25804 2026-01-27 cs.LG cs.AI cs.NI 74%

CardioForest: An Explainable Ensemble Learning Model for Automatic Wide QRS Complex Tachycardia Diagnosis from ECG

CardioForest: 一种用于从ECG信号自动检测宽QRS复波心动过速的可解释集成学习模型

Vaskar Chakma, Ju Xiaolin, Heling Cao, Xue Feng, Ji Xiaodong, Pan Haiyan, Gao Zhan

机构 * School of Artificial Intelligence and Computer Science(人工智能与计算机科学学院) Nantong University(南通大学) College of Information Science and Engineering(信息科学与工程学院) Henan University of Technology(河南理工大学) Affiliated Hospital of Nantong University(南通大学附属医院)

专题命中 诊断辅助 :diagnosis(title);分类 cs.LG

AI总结 CardioForest通过集成学习和SHAP分析,实现了高准确率的宽QRS复波心动过速检测,具有良好的可解释性和临床应用价值。

Journal ref Journal of Intelligent Medicine and Healthcare 2026, 4, 37-86

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2505.15139 2026-01-27 cs.CV 74%

Unified Cross-Modal Attention-Mixer Based Structural-Functional Connectomics Fusion for Neuropsychiatric Disorder Diagnosis

统一的跨模态注意力-混合器基于结构-功能连接组融合的神经精神疾病诊断

Badhan Mazumder, Lei Wu, Vince D. Calhoun, Dong Hye Ye

机构 * Department of Computer Science, Georgia State University(计算机科学系,佐治亚州立大学) Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University(跨机构神经影像与数据科学转化研究中心(TReNDS),佐治亚州立大学、佐治亚理工学院和埃默里大学)

专题命中 诊断辅助 :diagnosis(title);分类 cs.CV

AI总结 本文提出ConneX方法,通过统一的跨模态注意力和MLP-Mixer实现结构-功能连接组的多模态融合,提升神经精神疾病诊断性能。

Comments Published in the Proceedings of the 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2025). IEEE Xplore. DOI: 10.1109/EMBC58623.2025.11254194

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2506.17977 2026-01-27 cs.LG cs.DB 57%

SliceGX: Layer-wise GNN Explanation with Model-slicing

SliceGX: 图神经网络的分层解释方法

Tingting Zhu, Tingyang Chen, Yinghui Wu, Arijit Khan, Xiangyu Ke

机构 * Zhejiang University(浙江大学) Case Western Reserve University(凯斯西储大学) Bowling Green State University(布里奇沃特州立大学)

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

AI总结 SliceGX是一种通过分层分析生成图神经网络解释的方法,能够逐步构建并维护子图以解释模型输出。

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2601.17290 2026-01-27 cs.CV cs.AI 57%

Dynamic Meta-Ensemble Framework for Efficient and Accurate Deep Learning in Plant Leaf Disease Detection on Resource-Constrained Edge Devices

动态元集成框架用于在资源受限边缘设备上高效准确的植物叶片疾病检测深度学习

Weloday Fikadu Moges, Jianmei Su, Amin Waqas

机构 * South West University Science and Technology, School of Computer Science and Technology(西南科技大学计算机科学与技术学院) South West University Science and Technology, School of Control and Information Engineering Technology(西南科技大学控制与信息工程学院)

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

AI总结 本文提出动态元集成框架,通过自适应加权机制在资源受限边缘设备上实现高精度植物疾病检测,实验表明其在分类准确率和计算效率方面均优于现有方法。

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2601.18132 2026-01-27 cs.AI 50%

RareAlert: Aligning heterogeneous large language model reasoning for early rare disease risk screening

RareAlert: 对齐异构大语言模型推理以实现早期罕见病风险筛查

Xi Chen, Hongru Zhou, Huahui Yi, Shiyu Feng, Hanyu Zhou, Tiancheng He, Mingke You, Li Wang, Qiankun Li, Kun Wang, Weili Fu, Kang Li, Jian Li

专题命中 诊断辅助 :diagnosis(abstract)

AI总结 RareAlert通过整合多个LLM推理并校准后生成单一模型,实现早期罕见病风险筛查,其AUC达到0.917,优于现有方法。

Comments 28 page, 3 figures

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