An automatic approach to assess biomechanical risk using machine learning algorithms and inertial sensors [0.03%]
基于机器学习算法和惯性传感器的生物力学风险自动评估方法
Giuseppe Prisco,Mario Cesarelli,Fabrizio Esposito et al.
Giuseppe Prisco et al.
Work-related musculoskeletal disorders represent a significant occupational health issue. These disorders encompass a range of conditions resulting from specific risk factors associate to manual material handling such as: intensity, repetit...
Artificial intelligence-based method for renal function automatic assessment of each kidney using plain computed tomography (CT) scans [0.03%]
基于人工智能的利用平扫CT进行肾功能自动定量评估方法
Rongchang Guo,Wei Xia,Feng Xu et al.
Rongchang Guo et al.
Separate renal function assessment is important in clinical decision making. The single-photon emission computed tomography is commonly used for the assessment although radioactive, tedious and of high cost. This study aimed to automaticall...
Accuracy of iodine quantification and CT numbers using split-filter dual-energy CT: influence of phantom diameter [0.03%]
分能谱CT碘量计量化精度及CT值受体模直径影响的实验研究
Masato Kiriki,Maiko Kishigami,Toshiyuki Sakai et al.
Masato Kiriki et al.
Dual-energy computed tomography (DECT) generates virtual monochromatic images (VMI) and material decomposition images (MDI), facilitating enhanced tissue contrast and quantitative material assessment. However, the accuracy of these measurem...
Monitoring of respiration and cardiorespiratory interactions from multichannel seismocardiography signals [0.03%]
基于多通道地震心电图信号的呼吸和心肺交互作用监测
Jessica Centracchio,Salvatore Parlato,Samuel E Schmidt et al.
Jessica Centracchio et al.
Seismocardiography (SCG) uses accelerometers to record cardiac-induced accelerations of the chest wall. Cardiorespiratory interactions cause changes in amplitude and morphology of the SCG signals. Accelerometers can also directly monitor re...
Integrating dielectric properties analysis and machine learning for accurate liver cancer identification and infiltration depth prediction [0.03%]
结合介电性质分析和机器学习实现准确的肝癌识别与浸润深度预测
Chunyou Ye,Xiao Wang,Wenxia Ju et al.
Chunyou Ye et al.
The study of dielectric properties (DPs) reveals significant differences between normal and liver cancer tissues. Although the open-ended coaxial probe (OCP) method is widely used for measuring DPs, tumor infiltration depth affects the meas...
Machine learning-assisted classification of lung cancer: the role of sarcopenia, inflammatory biomarkers, and PET/CT anatomical-metabolic parameters [0.03%]
机器学习辅助肺癌分类：肌少症、炎症生物标志物和PET/CT解剖-代谢参数的作用
Handan Tanyildizi-Kokkulunk,Goksel Alcin,Iffet Cavdar et al.
Handan Tanyildizi-Kokkulunk et al.
Accurate differentiation between non-cancerous, benign, and malignant lung cancer remains a diagnostic challenge due to overlapping clinical and imaging characteristics. This study proposes a multimodal machine learning (ML) framework integ...
FrnOBSA: fractional order-based spectral analysis for arrhythmia detection [0.03%]
基于分数阶谱分析的心律失常检测方法
Shikha Singhal,Manjeet Kumar
Shikha Singhal
A comparative evaluation of surface dose values: radiochromic film measurements versus computational predictions from different radiotherapy planning algorithms [0.03%]
不同类型放射治疗计划算法的表面剂量比较评估： radioschromic 膜测量与计算机预测
Ibrahim Kaptan,Yucel Akdeniz,Emine Burcin Ispir
Ibrahim Kaptan
Accurate prediction of surface doses is crucial for clinical outcomes in radiotherapy. Surface dose distribution must be predicted accurately by calculation algorithms in the treatment planning system (TPS). This study aims to compare surfa...
Coplanar DCA-based hypofractionated stereotactic radiotherapy for very small brain metastasis from non-small cell lung cancer: treatment planning comparison with coplanar VMAT and preliminary clinical outcome [0.03%]
共面DCA基低分数立体定向放射治疗很小的非小细胞肺癌脑转移瘤：与共面VMAT治疗计划比较及初步临床结果
Shipai Zhu,An Li,Jia Liu et al.
Shipai Zhu et al.
To assess the clinical outcome of single-arc coplanar dynamic conformal arc (C-DCA) in three-fraction hypofractionated stereotactic radiotherapy (3F-HSRT) for single very small brain metastasis (BM; gross tumor volume [GTV] ≤ 1 cm3) from n...
An explainable machine learning (XAI) framework to enhance types of cardiovascular disease diagnosis and prognosis [0.03%]
一种可解释的机器学习(XAI)框架 以增强心血管疾病类型的诊断和预后
K Adalarasu,B Raghavan,B Madhavan et al.
K Adalarasu et al.
The World Health Organisation 2024 report shows that Cardiovascular Disease (CVD) is the leading cause of death worldwide, estimated at 17.9 million deaths annually, and its mortality is about 32% of all deaths in the world. Of these, about...