Predicting joint loading in Asian overweight and obese females with flexible flatfoot: a regression analysis of anthropometric parameters and gait dynamics [0.03%]
基于形态参数和步态动力学的亚洲肥胖女性扁平足共线负荷预测：回归分析
Linjuan Wei,Guoxin Zhang,Tony Lin-Wei Chen et al.
Linjuan Wei et al.
Current methods for obtaining accurate joint loading data lack simplicity, efficiency, and cost-effectiveness. This study aims to generate joint loading prediction models using anthropometric parameters and walking speed in overweight or ob...
Multi-task and multi-scale attention network for lymph node metastasis prediction in esophageal cancer [0.03%]
食管癌淋巴结转移预测的多任务和多尺度注意力网络
Yan Yi,Jiacheng Wang,Zhenjiang Li et al.
Yan Yi et al.
The accurate diagnosis of lymph node metastasis in esophageal squamous cell carcinoma is crucial in the treatment workflow, and the process is often time-consuming for clinicians. Recent deep learning models predicting whether lymph nodes a...
Hybrid adaptive attention deep supervision-guided U-Net for breast lesion segmentation in ultrasound computed tomography images [0.03%]
用于超声断层融合图像中乳腺病灶分割的混合自适应注意力深度监督引导U网模型
Xu Liu,Liang Zhou,Mengyuan Cai et al.
Xu Liu et al.
Breast cancer is the second deadliest cancer among women after lung cancer. Though the breast cancer death rate continues to decline in the past 20 years, the stages IV and III breast cancer death rates remain high. Therefore, an automated ...
Real-time estimations of blood glucose concentrations from sweat measurements using the local density random walk model [0.03%]
基于局部密度随机游走模型从汗液检测实时估计血糖浓度
Xiaoyu Yin,Elisabetta Peri,Eduard Pelssers et al.
Xiaoyu Yin et al.
Sweat provides a non-invasive alternative to blood draws, enabling glucose-concentration monitoring for both healthy individuals and diabetic patients. In our previous work, we demonstrated a strategy that accurately estimates blood glucose...
Stacked ensemble-based mutagenicity prediction model using multiple modalities with graph attention network [0.03%]
基于堆叠集成的多模态分子致突变性预测模型及图注意力网络方法
Tanya Liyaqat,Tanvir Ahmad,Mohammad Kashif et al.
Tanya Liyaqat et al.
Mutagenicity is concerning due to its link to genetic mutations, which can lead to cancer and other adverse effects. Early identification of mutagenic compounds in drug development is crucial to prevent unsafe candidates and reduce costs. W...
MSFHNet: a hybrid deep learning network for multi-scale spatiotemporal feature extraction of spatial cognitive EEG signals in BCI-VR systems [0.03%]
MSFHNet：一种用于BCI-VR系统中空间认知EEG信号多尺度时空特征提取的混合深度学习网络
Xulong Liu,Ziwei Jia,Meng Xun et al.
Xulong Liu et al.
The integration of brain-computer interface (BCI) and virtual reality (VR) systems offers transformative potential for spatial cognition training and assessment. By leveraging artificial intelligence (AI) to analyze electroencephalogram (EE...
A novel approach to exercise heart rate estimation combining PPG quality assessment with DNN modeling [0.03%]
结合PPG质量评估与DNN建模的运动心率估计新方法
Mengshan Wu,Xiang Chen
Mengshan Wu
This paper proposes a novel approach for exercise heart rate (HR) estimation by integrating PPG quality assessment with deep neural network (DNN) modeling. A frequency-domain kurtosis (kurtF) metric is introduced to identify high-quality PP...
Self-knowledge distillation for prediction of breast cancer molecular subtypes based on digital breast tomosynthesis [0.03%]
基于数字乳腺断层合成的乳腺癌分子亚型自我知识蒸馏预测方法研究
Wei Guo,Jiayi Bo,Shilin Chen et al.
Wei Guo et al.
This study aims to investigate the effectiveness of self-knowledge distillation (self-KD) with progressive refinement in the early prediction of molecular subtypes of breast cancer (BC) using digital breast tomosynthesis (DBT) images. This ...
Auxiliary classifier adversarial networks with maximum subdomain discrepancy for EEG-based emotion recognition [0.03%]
具有最大子域差异的辅助分类器对抗网络在基于EEG的情绪识别中的应用
Zhaowen Xiao,Qingshan She,Feng Fang et al.
Zhaowen Xiao et al.
Domain adaptation (DA) is considered to be effective solutions for unsupervised emotion recognition cross-session and cross-subject tasks based on electroencephalogram (EEG). However, the cross-domain shifts caused by individual differences...
Towards understanding the functional connectivity patterns in visual brain network [0.03%]
探究视觉脑网络的功能连接模式
Debanjali Bhattacharya,Neelam Sinha
Debanjali Bhattacharya
Recent advances in neuroimaging have enabled studies in functional connectivity (FC) of human brain, alongside investigation of the neuronal basis of cognition. One important FC study is the representation of vision in human brain. The rele...