Automatic classification of circulating blood cell clusters based on multi-channel flow cytometry imaging [0.03%]
基于多通道流动细胞成像的循环血细胞聚类自动分类
Suqiang Ma,Subhadeep Sengupta,Yao Lee et al.
Suqiang Ma et al.
Circulating blood cell clusters (CCCs) containing red blood cells (RBCs), white blood cells (WBCs), and platelets are significant biomarkers linked to pathological conditions like thrombosis, infection, and inflammation. Flow cytometry, pai...
An explainable deep learning approach for sleep staging in sleep apnea patients across all age subgroups from pulse oximetry signals [0.03%]
基于脉搏氧饱和度信号的阻塞性睡眠呼吸暂停患者各年龄段睡眠分期的可解释深度学习方法
Fernando Vaquerizo-Villar,Gonzalo C Gutiérrez-Tobal,Daniel Álvarez et al.
Fernando Vaquerizo-Villar et al.
Deep-learning (DL) approaches have been developed using pulse rate (PR) and blood oxygen saturation (SpO2) recordings from pulse oximetry to streamline sleep staging, particularly for obstructive sleep apnea (OSA) patients. However, lack of...
Interpretable manifold learning for T-wave alternans assessment with electrocardiographic imaging [0.03%]
基于心电图像的T波交替可解释流形分析方法
E Sánchez-Carballo,F M Melgarejo-Meseguer,R Vijayakumar et al.
E Sánchez-Carballo et al.
T-wave alternans (TWA) is a biomarker for sudden cardiac death prediction, characterized by subtle variations in the amplitude or morphology of consecutive T-waves in electrocardiographic studies. Electrocardiographic imaging (ECGI) offers ...
A hierarchical network model for the estimate of the energy expenditure in individuals with type 1 diabetes [0.03%]
用于估计1型糖尿病患者能量消耗的分层网络模型
Eleonora M Aiello,Chiara Toffanin,Michael C Riddell et al.
Eleonora M Aiello et al.
Total daily energy expenditure (TDEE) is impacted by many medical conditions, such as diabetes. In the case of type 1 diabetes (T1D), individuals need to have an accurate assessment of the energy expenditure in real-time to avoid dietary im...
Uncertainty- and hardness-weighted loss functions for medical image segmentation [0.03%]
不确定性加权和难度加权的损失函数在医学图像分割中的应用研究
Yanyan Zheng,Yabo Wu,Jie Chen et al.
Yanyan Zheng et al.
Accurate segmentation of medical images is essential for various image processing tasks and is now predominantly achieved using deep learning techniques. However, existing approaches often employ loss functions that fail to account for pixe...
A computation-efficient network with feature aggregation for cancer subtype classification on histopathological images [0.03%]
一种高效的基于特征聚合的癌症亚型分类网络方法
Zong Fan,Chaojie Zhang,Lulu Sun et al.
Zong Fan et al.
Histopathology whole-slide images (WSI) capture detailed structural and morphological features of tumor tissue, offering rich histological and molecular information. Deep learning (DL) methods have emerged to assist in automatically examini...
Effective Prediction of Drug Transport in a Partially Liquefied Vitreous Humor: Physics-informed Neural Network Modeling for Irregular Liquefaction Geometry [0.03%]
基于物理的神经网络模型在不规则液化几何体中有效预测部分液化的玻璃体药物传输问题
Shuqi Zhang,Anita Penkova,Xiaodong Jia et al.
Shuqi Zhang et al.
As the medium for intravitreal drug delivery, the vitreous body can significantly influence drug delivery because of various possible liquefaction geometries. This work innovatively proposes a varying-porosity approach that is capable of so...
COVID-19 symptom identification using Deep Learning and hardware emulated systems [0.03%]
使用深度学习和硬件仿真系统的COVID-19症状识别技术
Rashini Liyanarachchi,Janaka Wijekoon,Manujaya Premathilaka et al.
Rashini Liyanarachchi et al.
The COVID-19 pandemic disrupted regular global activities in every possible way. This pandemic, caused by the transmission of the infectious Coronavirus, is characterized by main symptoms such as fever, fatigue, cough, and loss of smell. A ...
Guohui Li,Jin Lu,Kang Chen et al.
Guohui Li et al.
With the emergence of new mutant corona virus disease 2019 (COVID-19) strains such as Delta and Omicron, the number of infected people in various countries has reached a new high. Accurate prediction of the number of infected people is of f...
Topological Persistence Guided Knowledge Distillation for Wearable Sensor Data [0.03%]
拓扑持续性引导的知识精馏在可穿戴传感器数据中的应用
Eun Som Jeon,Hongjun Choi,Ankita Shukla et al.
Eun Som Jeon et al.
Deep learning methods have achieved a lot of success in various applications involving converting wearable sensor data to actionable health insights. A common application areas is activity recognition, where deep-learning methods still suff...