Evaluating visco-hyperelastic mechanical responses of hydrogel-based scaffolds and their potential for biomechanical restoration of the human mandibular joint [0.03%]
基于水凝胶的支架的粘超弹性力学响应评价及其在人类下颌关节生物力学恢复中的潜在作用
Daniel Fidalgo,Pedro Rebolo,Marcelo Costa et al.
Daniel Fidalgo et al.
This study researches the viscous and hyperelastic mechanical behaviors of hydrogel-based nanocomposite materials, including: (i) a composite of human methacryloyl platelet lysate (hPLMA), human platelet lysates (hPL), and nanohydroxyapatit...
Yujin Choo,Seungjin Na,Eunok Paek
Yujin Choo
Post-translational modifications (PTMs) play critical roles in regulating cellular processes such as signal transduction, cell growth, and differentiation. Accurate identification of PTM sites is fundamental to understanding cellular mechan...
Advanced concept for identifying chemico-biological interactions associated with programmed cell death using a multi-scale attention residual convolutional neural network [0.03%]
基于多尺度注意力残差卷积神经网络的与程序性细胞死亡相关的化学生物相互作用识别方法研究
Igor V Pantic,Jovana Paunovic Pantic
Igor V Pantic
Early detection of programmed cell death (apoptosis) remains a significant challenge in microscopy and cell biology, particularly when relying on subtle nuclear texture changes observed in stained micrographs. Traditional machine learning m...
An optimized framework for Parkinson's disease classification using multimodal neuroimaging data with ensemble-based and data fusion networks [0.03%]
基于集成和数据融合网络的帕金森病多模态影像分类优化框架
Abdulaziz Alorf
Abdulaziz Alorf
Parkinson's disease (PD) is a neurodegenerative disease that affects both the motor and nonmotor functions of an individual and is more prevalent in older adults. PD is preceded by an early stage called prodromal PD, which starts very early...
FedStenoNet: tackling domain shift in x-ray coronary angiography through a personalized federated detection framework [0.03%]
FedStenoNet：通过个性化联合检测框架解决X射线冠状动脉造影中的领域变化问题
Mariachiara Di Cosmo,Giovanna Migliorelli,Francesca Pia Villani et al.
Mariachiara Di Cosmo et al.
Background and objective: The automatic identification of coronary stenosis in x-ray coronary angiography (XCA) is hindered by the variability in imaging protocols and patient characteristics across different hospitals, l...
CKS2 is overexpressed in high-grade and recurrent meningiomas and functions as an oncogene via the CKS2/miR-26a/miR-101 axis [0.03%]
CKS2在高级别和复发脑膜瘤中的过表达及其通过CKS2/miR-26a/miR-101轴发挥致癌作用的功能
Anuja Sharma,Ritanksha Joshi,Deepshikha Shahdeo et al.
Anuja Sharma et al.
Meningiomas are among the most common CNS tumors, typically benign (WHO grade 1) but with increasing malignancy in higher grades (2 and 3). Currently, there are no therapeutic alternatives for meningioma apart from surgery and radiotherapy....
Use of machine learning for predicting stress episodes based on wearable sensor data: A systematic review [0.03%]
基于可穿戴传感器数据使用机器学习预测应激发作的系统综述
António Oseas Pataca,Eftim Zdravevski,Paulo Jorge Coelho et al.
António Oseas Pataca et al.
Objective: This study consists of a systematic literature review that aims to explore the potential of integrating wearable sensor data and machine learning (ML) techniques for predicting stress episodes. It aims to ident...
A mechanistic modeling framework to interpret ACTH stimulation tests across HPA axis adaptation states and glucocorticoid feedback dynamics [0.03%]
一种解释HPA轴适应状态和糖皮质激素反馈动力学的ACTH刺激试验的机制模型框架
Mamta Yadav,Phool Singh
Mamta Yadav
The hypothalamic pituitary adrenal (HPA) axis is a key regulatory system coordinating endocrine responses to physiological and psychological stress. While the ACTH stimulation test remains a cornerstone of adrenal function assessment, its i...
A novel multimodal self-supervised framework for ECG arrhythmia classification [0.03%]
一种新颖的多模态自监督框架用于心电图心律失常分类
Jianqiang Hu,Cheng Li,Jinde Cao et al.
Jianqiang Hu et al.
The electrocardiogram (ECG) has emerged as a primary tool in clinical practice for identifying cardiovascular diseases, owing to its low cost, simplicity, and non-invasiveness. Given the high cost associated with acquiring a substantial amo...
Quantitative assessment of impact of technical and population-based factors on fairness of AI models for chest X-ray scans [0.03%]
基于技术和人口因素的定量评估胸部X光片AI模型公正性的影响
Dmitry Cherezov,Pingfu Fu,Anant Madabhushi
Dmitry Cherezov
Ensuring fairness in diagnostic AI models is essential for their safe deployment in clinical practice. This study investigates fairness by jointly analyzing population-based factors (sex and race) and technical factors (imaging site and X-r...