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...
Synthetic Data Generation via Generative Adversarial Networks in Healthcare: A Systematic Review of Image- and Signal-Based Studies [0.03%]
基于生成对抗网络的医疗保健中的合成数据生成：图像和信号研究的系统回顾
Muhammed Halil Akpinar,Abdulkadir Sengur,Massimo Salvi et al.
Muhammed Halil Akpinar et al.
Generative Adversarial Networks (GANs) have emerged as a powerful tool in artificial intelligence, particularly for unsupervised learning. This systematic review analyzes GAN applications in healthcare, focusing on image and signal-based st...
Miniaturized Devices for Isothermal Amplification and Photometric Quantification of Pseudomonas Aeruginosa [0.03%]
铜绿假单胞菌等温扩增和光电量化的微型装置
P Ramya Priya,Satish Kumar Dubey,Sanket Goel
P Ramya Priya
Goal: This study introduced a proof-of-concept prototype for isothermal recombinase polymerase amplification (RPA) with miniaturized photometric detection, enabling rapid P. aeruginosa detection. Methods: The researchers conducted the ampli...
Voxel-Wise Brain Graphs From Diffusion MRI: Intrinsic Eigenspace Dimensionality and Application to Functional MRI [0.03%]
基于扩散MRI的体素脑图谱：内在本征空间维度及其在功能磁共振成像中的应用
Hamid Behjat,Anjali Tarun,David Abramian et al.
Hamid Behjat et al.
Goal: Structural brain graphs are conventionally limited to defining nodes as gray matter regions from an atlas, with edges reflecting the density of axonal projections between pairs of nodes. Here we explicitly model the entire set of voxe...
Sleep Apnea Events Recognition Based on Polysomnographic Recordings: A Large-Scale Multi-Channel Machine Learning approach [0.03%]
基于多导睡眠图记录的睡眠呼吸事件识别：一种大规模多通道机器学习方法
Nicolo La Porta,Stefano Scafa,Michela Papandrea et al.
Nicolo La Porta et al.
Goal: The gold standard for detecting the presence of apneic events is a time and effort-consuming manual evaluation of type I polysomnographic recordings by experts, often not error-free. Such acquisition protocol requires dedicated facili...