Strain energy in human tibia during different exercises with adjustable leg weights: a subject-specific computational model analysis [0.03%]
不同锻炼方式下人类胫骨的应变能分析（带可调腿部配重）：基于特定对象的计算模型分析
Xuan Guo,XinSheng Xu,Xiang Geng et al.
Xuan Guo et al.
Physical exercise is recommended to improve tibia strength, a common site for stress injuries, while identifying optimal training regimens remains a significant challenge. This study investigated tibial responses to varied exercise regimens...
Hybrid model of feature-driven modular neural network-based grasshopper optimization algorithm for diabetic retinopathy classification using fundus images [0.03%]
基于特征驱动模块化神经网络的混合草履虫优化算法在眼底图像下糖尿病视网膜病变分类研究
D Binny Jeba Durai,T Jaya
D Binny Jeba Durai
Diabetic retinopathy (DR) is a progressive condition that can lead to blindness if undiagnosed or untreated. Automatic systems for DR prediction using fundus images have been developed, but challenges like variable illumination, overfitting...
OCCMNet: Occlusion-Aware Class Characteristic Mining Network for multi-class artifacts detection in endoscopy [0.03%]
OCCMNet：内窥镜多分类人工制品检测的遮挡感知类特征挖掘网络
Chenchu Xu,Yu Chen,Jie Liu et al.
Chenchu Xu et al.
Multi-class endoscope artifacts detection is crucial for eliminating interference caused by artifacts during clinical examinations and reducing the rate of misdiagnosis and missed diagnoses by physicians. However, this task remains challeng...
Comprehensive comparison of different BITA graft configurations: a computational study integrating TTFM and hemodynamic predictors [0.03%]
不同BITA移植物配置的综合比较：结合TTFM和血液动力学预测因子的计算研究
Ahmad Masoudi,Hossein Ali Pakravan
Ahmad Masoudi
Bilateral internal thoracic artery (BITA) grafting utilizes both the left (LITA) and right (RITA) internal thoracic arteries simultaneously and is recommended in the literature. However, the optimal configuration for BITA grafting remains u...
New AI explained and validated deep learning approaches to accurately predict diabetes [0.03%]
新的人工智能解释并验证了深度学习在准确预测糖尿病方面的应用方法
Ifra Shaheen,Nadeem Javaid,Nabil Alrajeh et al.
Ifra Shaheen et al.
Diabetes is a metabolic condition that can lead to chronic illness and organ failure if it remains untreated. Accurate detection is essential to reduce these risks at an early stage. Recent advancements in predictive models show promising r...
ETDformer: an effective transformer block for segmentation of intracranial hemorrhage [0.03%]
ETDformer：用于颅内出血分割的有效变压器模块
Wanyuan Gong,Yanmin Luo,Fuxing Yang et al.
Wanyuan Gong et al.
Intracerebral hemorrhage (ICH) medical image segmentation plays a crucial role in clinical diagnostics and treatment planning. The U-Net architecture, known for its encoder-decoder design and skip connections, is widely used but often strug...
Estimation of pulse wave analysis indices from invasive arterial blood pressure only for a clinical assessment of wave reflection in a 5-day septic animal experiment [0.03%]
仅根据侵入性动脉血压估算脉波分析指标以在五天的脓毒症动物实验中对波反射进行临床评估
Diletta Guberti,Manuela Ferrario,Marta Carrara
Diletta Guberti
Wave separation analysis (WSA) is the gold standard to analyze the arterial blood pressure (ABP) waveform, decomposing it into a forward and a reflected wave. It requires ABP and arterial blood flow (ABF) measurement, and ABF is often unava...
Automatic placement of simulated dental implants within CBCT images in optimum positions: a deep learning model [0.03%]
在CBCT图像中最佳位置自动放置模拟牙科种植体：深度学习模型
Shahd Alotaibi,Mona Alsomali,Shatha Alghamdi et al.
Shahd Alotaibi et al.
Implant dentistry is the standard of care for the replacement of missing teeth. It is a complex process where cone-beam computed tomography (CBCT) images are analyzed by the dentist to determine the implants' length, diameter, and position,...
M4S-Net: a motion-enhanced shape-aware semi-supervised network for echocardiography sequence segmentation [0.03%]
M4S-Net：用于回声心电图序列分割的运动增强形状感知半监督网络
Mingshan Li,Fangyan Tian,Shuyu Liang et al.
Mingshan Li et al.
Sequence segmentation of echocardiograms is of great significance for the diagnosis and treatment of cardiovascular diseases. However, the low quality of ultrasound imaging and the complexity of cardiac motion pose great challenges to it. I...
LGENet: disentangle anatomy and pathology features for late gadolinium enhancement image segmentation [0.03%]
LGENet：解剖与病理特征分离在钆延迟增强图像分割中的应用
Mingjing Yang,Kangwen Yang,Mengjun Wu et al.
Mingjing Yang et al.
Myocardium scar segmentation is essential for clinical diagnosis and prognosis for cardiac vascular diseases. Late gadolinium enhancement (LGE) imaging technology has been widely utilized to visualize left atrial and ventricular scars. Howe...