Mimicking nuclear mechanics in stem cell adhesion on curved rigid substrates using flat soft substrates [0.03%]
利用平坦的软基质模仿干细胞在弯曲刚性基底上的核机械特性
Lorenzo Santoro,Óscar L Rodríguez-Montaño,Luciano Lamberti et al.
Lorenzo Santoro et al.
Background and objective: In vitro culture systems are widely used in cell-based research, yet they predominantly rely on flat substrates that fail to capture the curved mechanical landscapes encountered by cells in vivo....
Computational screening of natural compounds reveals glycyrrhisoflavone as a potential Hepatitis B X-interacting protein inhibitor [0.03%]
计算筛选天然化合物发现甘草异黄酮为潜在的乙肝X相互作用蛋白抑制剂
Md Naimul Haque Shohan,Mahir Azmal,Omar Faruk Talukder et al.
Md Naimul Haque Shohan et al.
Background and objective: Hepatitis B virus (HBV) remains a major global health burden, affecting ∼296 million people worldwide. Chronic infection can progress to liver cirrhosis and hepatocellular carcinoma (HCC), partl...
Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences [0.03%]
基于长序列的RNA假尿苷修饰位点预测元分类器Meta-PseU
Takumi Suto,Md Harun-Or-Roshid,Hiroyuki Kurata
Takumi Suto
Background and objectives: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates transla...
Benchmarking deep learning architectures for hyperspectral in-vivo brain tumor segmentation [0.03%]
深度学习架构在体外脑肿瘤分割的超光谱基准测试
Guillermo Vazquez,Domenico Ragusa,Emanuele Torti et al.
Guillermo Vazquez et al.
Background and objective: Deep Learning (DL) has become increasingly relevant in medical image analysis, especially for tasks such as surgical guidance. In this respect, Hyperspectral Imaging (HSI) has shown encouraging r...
Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS [0.03%]
基于强化学习的动态集成方法用于错义变异效应预测及多级变异优先排序
Syed Hassan Abbas,Jun Wu,Tieliu Shi
Syed Hassan Abbas
Background: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often requ...
BMR-Restormer: A transformer-based blind inpainting network for ultrasound marker removal [0.03%]
基于变压器的盲图修补网络用于超声标记清除
Jiabin Yu,Hongmei Mi,Dong Chen et al.
Jiabin Yu et al.
Background and objectives: Artificial markers, including crosses, text, and measurement lines, are commonly embedded in clinical ultrasound images to aid visual diagnosis. However, these overlays introduce substantial bia...
Information bottleneck-driven Gaussian PID enables modality-level interpretability in multimodal survival prediction [0.03%]
信息瓶颈驱动的高斯PID enabled模态级别多模态生存预测的可解释性
Zeruo Yang,Shiqi Wu,Shujian Yu
Zeruo Yang
Background and objective: Multimodal survival analysis is essential for precision oncology, yet existing interpretability methods cannot distinguish whether modalities provide shared, modality-specific, or jointly emergen...
Interpretable Machine Learning Model Using Oxygenation and Respiratory Variability to Predict Hemorrhagic Stroke Mortality: A Multicenter Validation Study [0.03%]
一项使用氧合和呼吸变异预测出血性卒中死亡率的可解释机器学习模型的多中心验证研究
Jing Feng,Hongyu Zhang,Jianheng Gu et al.
Jing Feng et al.
Background: Hemorrhagic stroke has high in-hospital mortality, but early risk prediction remains suboptimal. While prior studies have focused on ventilation strategies and mechanical support, limited research has explored...
Global and local pseudo-label filtering for semi-supervised carotid plaque classification from ultrasound [0.03%]
全局和局部伪标签筛选的半监督下颈动脉斑块超声分类方法
Ran Zhou,Wei Deng,Wenjie Yu et al.
Ran Zhou et al.
Background and objectives: Vulnerable carotid plaques can lead to stroke or TIA; thus, classifying these plaques by ultrasound is crucial. Deep learning improves classification, but requires large labeled datasets, and ex...
Adaptive graph convolutional neural network incorporating ECG for individualized motor imagery EEG classification [0.03%]
基于ECG的心电图自适应图卷积神经网络在个体化运动想象EEG分类中的应用
Songping Li,Gan Luo,Lixue Zhou et al.
Songping Li et al.
Background and objective: The recognition of motor imagery electroencephalogram (EEG) signals, which non-invasively capture the macroscopic electrical activity of the brain, is critical for medical rehabilitation and inte...