Md Zabirul Islam,Ge Wang
Md Zabirul Islam
Avatars in the educational metaverse are revolutionizing the learning process by providing interactive and effective learning experiences. These avatars enable students to engage in realistic scenarios, work in groups, and develop essential...
Radiographic prediction model based on X-rays predicting anterior cruciate ligament function in patients with knee osteoarthritis [0.03%]
基于X射线的放射学预测模型在膝关节骨关节炎患者中的前交叉韧带功能预测价值
Guanghan Gao,Yaonan Zhang,Lei Shi et al.
Guanghan Gao et al.
Knee osteoarthritis (KOA) is a prevalent chronic condition in the elderly and is often associated with instability caused by anterior cruciate ligament (ACL) degeneration. The functional integrity of ACL is crucial for the diagnosis and tre...
Artificial intelligence-assisted diagnosis of early allograft dysfunction based on ultrasound image and data [0.03%]
基于超声图像和数据的智能辅助早期移植物功能障碍诊断技术研究
Yaqing Meng,Mingyang Wang,Ningning Niu et al.
Yaqing Meng et al.
Early allograft dysfunction (EAD) significantly affects liver transplantation prognosis. This study evaluated the effectiveness of artificial intelligence (AI)-assisted methods in accurately diagnosing EAD and identifying its causes. The pr...
Artificial intelligence in retinal image analysis for hypertensive retinopathy diagnosis: a comprehensive review and perspective [0.03%]
人工智能在高血压视网膜病变图像分析中的应用：全面回顾与展望
Rajendra Kankrale,Manesh Kokare
Rajendra Kankrale
Hypertensive retinopathy (HR) occurs when the choroidal vessels, which form the photosensitive layer at the back of the eye, are injured owing to high blood pressure. Artificial intelligence (AI) in retinal image analysis (RIA) for HR diagn...
LViT-Net: a domain generalization person re-identification model combining local semantics and multi-feature cross fusion [0.03%]
LViT-Net：结合局部语义和多特征交叉融合的域泛化行人重识别模型
Xintong Hu,Peishun Liu,Xuefang Wang et al.
Xintong Hu et al.
In the task of domain generalization person re-identification (ReID), pedestrian image features exhibit significant intra-class variability and inter-class similarity. Existing methods rely on a single feature extraction architecture and st...
Visual explainable artificial intelligence for graph-based visual question answering and scene graph curation [0.03%]
基于图的视觉问答和场景图可视化的可解释人工智能
Sebastian Künzel,Tanja Munz-Körner,Pascal Tilli et al.
Sebastian Künzel et al.
This study presents a novel visualization approach to explainable artificial intelligence for graph-based visual question answering (VQA) systems. The method focuses on identifying false answer predictions by the model and offers users the ...
Bootstrapping BI-RADS classification using large language models and transformers in breast magnetic resonance imaging reports [0.03%]
基于大规模语言模型和变压器的乳腺MRI报告中BI-RADS分类的自助法分析
Yuxin Liu,Xiang Zhang,Weiwei Cao et al.
Yuxin Liu et al.
Breast cancer is one of the most common malignancies among women globally. Magnetic resonance imaging (MRI), as the final non-invasive diagnostic tool before biopsy, provides detailed free-text reports that support clinical decision-making....
Nucleus pulposus clamping procedures based on optimized material point method for surgical simulation systems [0.03%]
基于优化MPM的核钳夹过程仿真在手术模拟系统中的应用
Jianlong Ni,Jingrong Li,Zhiyuan Xie et al.
Jianlong Ni et al.
Clamping and removal of the nucleus pulposus (NP) are critical operations during transforaminal endoscopic lumbar discectomy. To meet the challenge of simulating the NP in real-time for better training output, an improved material point met...
PCRFed: personalized federated learning with contrastive representation for non-independently and identically distributed medical image segmentation [0.03%]
PCRFed：用于非独立同分布医学图像分割的对比表示个性化联合学习
Shengyuan Liu,Ruofan Zhang,Mengjie Fang et al.
Shengyuan Liu et al.
Federated learning (FL) has shown great potential in addressing data privacy issues in medical image analysis. However, varying data distributions across different sites can create challenges in aggregating client models and achieving good ...
Principal component analysis and fine-tuned vision transformation integrating model explainability for breast cancer prediction [0.03%]
结合模型可解释性的主成分分析和微调视觉变换在乳腺癌预测中的应用
Huong Hoang Luong,Phuc Phan Hong,Dat Vo Minh et al.
Huong Hoang Luong et al.
Breast cancer, which is the most commonly diagnosed cancers among women, is a notable health issues globally. Breast cancer is a result of abnormal cells in the breast tissue growing out of control. Histopathology, which refers to the detec...