TwinRL-Onco: A World Model-Empowered Digital Twin Framework with Hierarchical Reinforcement Learning for Venetoclax Resistance Trajectory Prediction and Adaptive Therapy Optimization in Chronic Lymphocytic Leukemia [0.03%]
基于分层强化学习的数字孪生框架预测慢性淋巴细胞白血病患者对维奈克拉耐药性轨迹及适应性治疗优化(TwinRL-Onco)
Zi Wang,Chenghao Ge,Yufan Hu et al.
Zi Wang et al.
Chronic lymphocytic leukaemia (CLL) presents considerable therapeutic obstacles due to the development of treatment-resistant disease, especially with BCL-2 inhibitors like venetoclax, and is among the most challenging haematological malign...
Consistency-based Semi-supervised Evidential Active Learning Framework for Robust Classification of Radiology Images [0.03%]
基于一致性的半监督证据主动学习的放射影像 robust 分类框架
Shafa Balaram,Manh Cuong Nguyen,Yang Yu et al.
Shafa Balaram et al.
Deep learning offers high performance for radiology image classification, but relies on large, expert annotated datasets. Semi-supervised learning and active learning approaches can leverage unlabelled samples and mitigate the annotation bu...
CTransFuse: A Hybrid Transformer-CNN Framework for Precise Meniscus Segmentation and Lesion Identification [0.03%]
CTransFuse：一种用于精准半月板分割和病变识别的Transformer-CNN混合框架
Yane Li,Qinuo Zhang,Wenjing Wang et al.
Yane Li et al.
Meniscal tears and degenerative changes are the most common pathologies affecting the knee joint. In magnetic resonance imaging (MRI), these lesions often manifest at small spatial scales with indistinct boundaries and heterogeneous intensi...
SDMCC: Sample-wise Debiased Multilevel Contrastive Clustering for Single-cell Gene Expression Data [0.03%]
基于样本的单细胞基因表达数据去偏多级对比聚类方法
Han Xiao,Dayu Hu,Fengyue Zhang et al.
Han Xiao et al.
Single-cell gene expression profiling has emerged as a powerful technology for dissecting complex tissues at unprecedented resolution. Accurate cell clustering is a fundamental computational prerequisite for cell type identification. In rec...
HepaCopilot: A 6G-Enabled Multimodal Vision-Language Agent for Real-Time Hepatocellular Carcinoma Risk Stratification via Contrast-Enhanced Ultrasonography with Chain-of-Thought Clinical Reasoning [0.03%]
HepaCopilot：一种基于6G的多模态视觉语言代理，通过增强超声波进行实时肝细胞癌风险分层并结合临床推理链思维
Hong Jin,Yang Zhou,Shaowei Ma et al.
Hong Jin et al.
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths around the world. One major barrier to detecting HCC is that CEUS is heavily reliant on operator interpretation, leading to an excessive amount of variabil...
An Adaptive Fusion Network for Breast Tumor Grading Based on Graph Structure Learning [0.03%]
一种基于图结构学习的乳腺肿瘤分级自适应融合网络方法研究
Lei Yang,Kang Li,Zhan Yu et al.
Lei Yang et al.
Breast cancer is a serious threat to women's life and health. Early grading of breast tumor malignancy is the key for improving patient survival rate. In clinical diagnosis, physicians often utilize multi-modal data information to accuratel...
Physics-Informed Prostate MR-US Registration by Biomechanical Fields Prediction Network [0.03%]
基于生物力学场预测网络的物理信息前列腺MR-US配准方法
Shixing Ma,Zhaoxi Lin,Xinzhe Du et al.
Shixing Ma et al.
Embedding biomechanical priors into medical image registration is essential to ensure physiologically credible soft-tissue motion. However, the optimal strategy for enforcing these priors within learning-based models re mains under-explored...
Knowledge-Augmented Spectral Hypergraph Learning for Protein Complex Identification in Network-Based Drug Discovery [0.03%]
基于网络的药物发现中用于蛋白质复合物识别的知识增强谱系超图学习
Weiyu Feng,Yixiang Zhang,Yeyuge Chen et al.
Weiyu Feng et al.
Protein complexes are fundamental modular units of cellular organization, and their accurate identification is critical for network-based drug discovery. However, most computational approaches rely on pairwise interactions or heuristic clus...
A Digital Twin-Inspired Closed-Loop Latent Simulation Framework for Cross-Cohort Breast Cancer Subtype Classification under Modality-Disjoint Learning [0.03%]
一种数字孪生启发的闭环潜在模拟框架，在模式不相交学习下的跨队列乳腺癌亚型分类
Nabil Hezil,Ahmed Bouridane,Rifat Hamoudi et al.
Nabil Hezil et al.
Breast cancer PAM50 subtype classification is hindered by the single-pass prediction paradigm of existing deep learning systems, which provide no mechanism for iterative representation refinement or uncertainty trajectory analysis. We prese...
Semi-supervised Medical Image Classification Made Easier with Causality-Driven Learning [0.03%]
基于因果驱动的半监督医学图像分类方法
Chuankai Xu,Junhao Li,Yan Liu et al.
Chuankai Xu et al.
Semi-supervised learning (SSL) has significantly improved medical image analysis, especially in cases with limited labeled data, by leveraging information from unlabeled data. Consistency regularization, a key method in SSL, promotes alignm...