Unveiling the impact of modified cell death models on hypofractionated radiation therapy efficacy [0.03%]
改良的细胞死亡模型对低分割放射治疗疗效影响的研究
Islam Sagov,Аида Arsenovna Сорокина,E S Sukhikh et al.
Islam Sagov et al.
Nowadays the linear-quadratic model (LQ) is the most used model to estimate the biological effective dose (BED) and the equivalent dose in 2 Gy fractions (EQD2) for different fractionation regimens. Nevertheless, it is debated of applicabil...
In-Vivo Reflection Terahertz Imaging for Non-Invasive Skin Diagnostics: A Topical Review [0.03%]
用于非侵入式皮肤诊断的太赫兹反射成像：综述
Naveen Sharma,Swetha Duvuri,Ashu Rastogi et al.
Naveen Sharma et al.
Medical imaging has revolutionized disease detection and patient care; however, conventional modalities such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), ultrasound, and optical imaging have inherent limitations in sensiti...
ECG Beat Classification with Fractional Order Differentiator and Machine Learning Techniques [0.03%]
基于分数阶微分器和模式识别的ECG心搏分类
H K Prasad Katamreddi,Tirumala Krishna Battula
H K Prasad Katamreddi
Electrocardiogram (ECG) is essential for assessing heart function, but manual analysis is time-consuming and error-prone. Automated ECG analysis can improve early detection of cardiovascular diseases by accurately identifying abnormal beats...
Cardiovascular Risk Prediction in Diabetes: A Hybrid Machine Learning Approach [0.03%]
糖尿病心血管风险预测的混合机器学习方法
Imran Rehan,Mujeeb Ur Rehman
Imran Rehan
Cardiovascular disease (CVD) is a major cause of morbidity and mortality in diabetic populations. Early detection of cardiovascular risk in diabetes is crucial to reduce complications, particularly in resource-limited settings. This study a...
Xiangyu Deng,Wenbo Dong,Zhecong Fan
Xiangyu Deng
Current infusion monitoring methods primarily rely on two technological approaches: nonvisual sensor technology and visual sensor technology, for real-time monitoring of the remaining liquid volume in infusion bottles within infusion scenar...
Optical scattering coefficient measurement of blood plasma during clot formation [0.03%]
血浆凝固过程中光学散射系数的测量
Lea Abi Nassif,Wadih Khater,Fabrice Pellen et al.
Lea Abi Nassif et al.

Venous Thromboembolism (VTE) is a very dangerous and common disease. While approximately 50% of VTE can be attributed to identifiable causes, the remaining half has no known origin and about 30% of this group show recurrence. Monitorin...
SCIMITAR: Optimising chest digital tomosynthesis devices using geometric simulations and genetic algorithms [0.03%]
基于几何仿真和遗传算法的优化胸部数字体层摄影设备项目
Alexander David Hill,Daliya Aflyatunova,Aquila Mavalankar et al.
Alexander David Hill et al.
Objective: Digital tomosynthesis (DT) bridges the gap between planar X-rays and computed tomography, offering rapid, low-dose 3D imaging. A mobile chest DT device could transform procedures such as nasogastric tube placem...
Remote Patient Monitoring System Combining Hardware and Artificial Intelligence Based Software [0.03%]
结合硬件和基于人工智能软件的远程患者监测系统
Kaan Kivircik,Sibel Çimen,Nilay Bulduk et al.
Kaan Kivircik et al.
This study details the development of a remote patient monitoring system with a primary focus on a novel, customized Deep Neural Network (DNN) for arrhythmia detection. The system integrates hardware for real-time data collection from biome...
Comparison of Quantitative Lung Measures in Low Dose Energy-Integrating Detector and Photon-Counting Detector Chest CT with an Anthropomorphic Phantom [0.03%]
低剂量能谱CT与光子计数探测器胸部CT肺量化测量的体模对比研究
Natally ALArab,Marrissa McIntosh,Junfeng Guo et al.
Natally ALArab et al.
Photon-counting detector (PCD) computed tomography (CT) promises improved resolution and contrast at reduced X-ray dose compared to energy-integrating detector (EID) CT. To determine the parameters that achieve robust accuracy of quantitati...
MEFD dataset and GCSFormer model : Cross-subject emotion recognition based on multimodal physiological signals [0.03%]
基于多模态生理信号的跨受试者情绪识别（MEFD数据集和GCSFormer模型）
Xiangyu Deng,Zhecong Fan,Wenbo Dong
Xiangyu Deng
Cross-subject emotion recognition is an important research direction in the fields of affective computing and brain-computer interfaces, aiming to identify the emotional states of different individuals through physiological signals such as ...