Context-Aware Dual-Task Deep Network for Concurrent Bone Segmentation and Clinical Assessment to Enhance Shoulder Arthroplasty Preoperative planning [0.03%]
上下文感知的双任务深度网络：通过肩关节置换术术前规划同时进行骨分割和临床评估以增强肩关节置换术的术前规划
Luca Marsilio,Andrea Moglia,Alfonso Manzotti et al.
Luca Marsilio et al.
Goal: Effective preoperative planning for shoulder joint replacement requires accurate glenohumeral joint (GH) digital surfaces and reliable clinical staging. Methods: xCEL-UNet was designed as a dual-task deep network for humerus and scapu...
The Shift to Over-the-Counter Diagnostic Testing After RADx: Clinical, Regulatory, and Societal Implications [0.03%]
RADx之后转向非处方诊断检测的临床、监管和社会影响
Maren Downing,John Broach,Wilbur Lam et al.
Maren Downing et al.
The National Institutes of Health's Rapid Acceleration of Diagnostics (RADx) program answered the call to accelerate the development of point-of-care (POC) and over-the-counter (OTC) COVID-19 tests. The widespread availability and access to...
Ensemble Deep Learning Object Detection Fusion for Cell Tracking, Mitosis, and Lineage [0.03%]
基于集成深度学习的目标检测细胞追踪、有丝分裂和谱系分析方法
Imad Eddine Toubal,Noor Al-Shakarji,D D W Cornelison et al.
Imad Eddine Toubal et al.
Cell tracking and motility analysis are essential for understanding multicellular processes, automated quantification in biomedical experiments, and medical diagnosis and treatment. However, manual tracking is labor-intensive, tedious, and ...
Design and Validation of a Tripping-Eliciting Platform Based on Compliant Random Obstacles [0.03%]
基于顺应性随机障碍的触发绊倒平台的设计与验证
Eugenio Anselmino,Lorenzo Pittoni,Tommaso Ciapetti et al.
Eugenio Anselmino et al.
Goal: The experimental study of the stumble phenomena is essential to develop novel technological solutions to limit harmful effects in at-risk populations. A versatile platform to deliver realistic and unanticipated tripping perturbations,...
An ECG-Based Model for Left Ventricular Hypertrophy Detection: A Machine Learning Approach [0.03%]
基于ECG的左心室肥厚检测模型：一种机器学习方法
Marion Taconne,Valentina D A Corino,Luca Mainardi
Marion Taconne
Goal: Despite the high incidence of left ventricular hypertrophy (LVH), clinical LVH-electrocardiography (ECG) criteria remain unsatisfactory due to low sensitivity. We propose an automatic LVH detection method based on ECG-extracted featur...
Marisse Masis Solano,Remy Dumas,Mark R Lesk et al.
Marisse Masis Solano et al.
Objective: To assess the impact of microgravity exposure on ocular rigidity (OR), intraocular pressure (IOP), and ocular pulse amplitude (OPA) following long-term space missions. OR was evaluated using optical coherence tomography (OCT) and...
Advancements in Clinical Evaluation and Regulatory Frameworks for AI-Driven Software as a Medical Device (SaMD) [0.03%]
人工智能驱动的医疗设备软件(SaMD)的临床评估和监管框架进展
Shiau-Ru Yang,Jen-Tzung Chien,Chen-Yi Lee
Shiau-Ru Yang
Owing to the rapid progress in artificial intelligence (AI) and the widespread use of generative learning, the problem of sparse data has been solved effectively in various research fields. The application of AI technologies has resulted in...
Sub-Chronic Peroneal Nerve Stimulation Lowers Ambulatory Blood Pressure in Spontaneously Hypertensive Rats [0.03%]
亚慢性腓神经刺激可降低自发性高血压大鼠的24小时血压变异性和日常活动量
K Romero,M A Gonzalez-Gonzalez,D Lloyd et al.
K Romero et al.
Objective: Acute electrical stimulation of the common peroneal nerve (cPNS) has been shown to cause an immediate reduction in systolic blood pressure (SBP) in spontaneous hypertense rats (SHR), but the effect of this treatment in sub-chroni...
Hybrid Deep Learning-Based Enhanced Occlusion Segmentation in PICU Patient Monitoring [0.03%]
基于混合深度学习的PICU患者监测中增强遮挡分割方法
Mario Francisco Munoz,Hoang Vu Huy,Thanh-Dung Le et al.
Mario Francisco Munoz et al.
Remote patient monitoring has emerged as a prominent non-invasive method, using digital technologies and computer vision (CV) to replace traditional invasive monitoring. While neonatal and pediatric departments embrace this approach, Pediat...
HCM-Echo-VAR-Ensemble: Deep Ensemble Fusion to Detect Hypertrophic Cardiomyopathy in Echocardiograms [0.03%]
基于深度集成融合的超声心动图心肌肥厚检测方法(HCM-Echo-VAR-Ensemble)
Abdulsalam Almadani,Atifa Sarwar,Emmanuel Agu et al.
Abdulsalam Almadani et al.
Goal: To detect Hypertrophic Cardiomyopathy (HCM) from multiple views of Echocardiogram (cardiac ultrasound) videos. Methods: we propose HCM-Echo-VAR-Ensemble, a novel framework that performs binary classification (HCM vs. no HCM) of echoca...