Clinical Evaluation of Novel Custom 3D-Printed Meshed-Silicone Orthotics Utilizing Standing Foot Scans and Dynamic Gait Data [0.03%]
基于站立足部扫描和动态步态数据的新型定制3D打印网状硅胶矫形器的临床评价
Joshua Kubach,Mario Pasurka,Julia Lueg et al.
Joshua Kubach et al.
Background: Conventional orthotic insoles demonstrate limited accommodation for individual foot morphology and plantar pressure distribution patterns, resulting in biomechanical inefficiencies and patient discomfort. Comp...
Computed tomography-derived radiomics models for distinguishing difficult-to-diagnose inflammatory and malignant pulmonary nodules [0.03%]
基于CT影像组学的模型鉴别难以诊断的肺部炎性结节及恶性结节
Shaohong Wu,Xiaoyan Wang,Wenli Shan et al.
Shaohong Wu et al.
Background: CT signs of inflammatory and malignant pulmonary nodules are shared and often confused, leading to difficulties in clinical differentiation. Previous relevant studies have neglected to explore the reclassifica...
Exploring the Landscape of Operating Room Scheduling: A Bibliometric Analysis of Recent Advancements and Future Prospects [0.03%]
operating room调度的文献计量分析：近期进展与未来前景探讨
Md Al Amin,Majed Hadid,Adel Elomri et al.
Md Al Amin et al.
Background: Operating Room Scheduling (ORS) is vital in healthcare management, impacting patient outcomes, economics, and the shift to value-based care. The academic literature offers various solutions with distinct pros ...
Sustainable E-Health: Energy-Efficient Tiny AI for Epileptic Seizure Detection via EEG [0.03%]
可持续的电子健康：通过EEG进行癫痫发作检测的节能微小AI
Moez Hizem,Mohamed Ould-Elhassen Aoueileyine,Samir Brahim Belhaouari et al.
Moez Hizem et al.
Tiny Artificial Intelligence (Tiny AI) is transforming resource-constrained embedded systems, particularly in e-health applications, by introducing a shift in Tiny Machine Learning (TinyML) and its integration with the Internet of Things (I...
RunicNet: Leveraging CNNs With Attention Mechanisms for Cervical Cancer Cell Classification [0.03%]
基于注意力机制的CNN宫颈癌细胞分类方法研究
Erin Beate Bjørkeli,Morteza Esmaeili
Erin Beate Bjørkeli
Introduction: Early detection through routine screening methods, such as the Papanicolaou (Pap) test, is crucial for reducing cervical cancer mortality. However, the Pap smear method faces challenges including subjective ...
Machine Learning based Model Reveals the Metabolites Involved in Coronary Artery Disease [0.03%]
基于机器学习的模型揭示了与冠状动脉疾病有关的代谢物
Fathima Lamya,Muhammad Arif,Mahbuba Rahman et al.
Fathima Lamya et al.
Introduction: Coronary artery disease (CAD) is a major global cause of morbidity and mortality. Therefore, advances in early identification and individualized treatment plans are crucial. ...
A Numerical Systematic Review and Meta-Analysis of Diagnosing the Vibration Modes of the Cylindrical Shell in the MRI Machine [0.03%]
一种数值系统综述和元分析诊断MRI机器中圆柱壳体的振动模式
Hamidreza Mortazavy Beni,Fatemeh Aghaei,Ashkan Heydarian et al.
Hamidreza Mortazavy Beni et al.
Magnetic Resonance Imaging (MRI) is a non-invasive imaging method that utilizes radio waves and magnetic fields. This study focuses on reducing the acoustic noise produced inside the cylindrical shell of the scanner, where the patient is lo...
Rib and Sternum Fractures From Falls: Global Burden of Disease and Predictions [0.03%]
跌落所致的肋骨和胸骨骨折：疾病负担及预测
Zhanghao Huang,Jun Zhu
Zhanghao Huang
Background: By combining existing Global Burden of Disease (GBD) data with the economic conditions of different regions, we can better understand disease trends and make more accurate estimations, facilitating effective p...
Analysis of Muscle Forces and Their Impact on Femoral Bone Stresses Using Response Surface Methodology (RSM) [0.03%]
响应面法(RSM)分析肌肉力及对股骨应力的影响
Saeed Habibi,Mohammad Nazari Shalkouhi,Mohammad Javad Keyhani Dehnavi et al.
Saeed Habibi et al.
In this study, reliability methods were demonstrated as a promising approach in medical engineering by identifying the most significant muscle forces affecting femoral stress. First, the finite element method (FEM) in Abaqus software was us...
An Enhanced Hybrid Model Combining CNN, BiLSTM, and Attention Mechanism for ECG Segment Classification [0.03%]
一种结合CNN、BiLSTM和注意力机制的ECG片段分类增强混合模型
Mechichi Najia,Benzarti Faouzi
Mechichi Najia
Deep learning models are necessary in the field of healthcare for the diagnosis of cardiac rhythm diseases since the conventional ECG classification is based on hand-crafted feature engineering and traditional machine learning. Nevertheless...