Advancing thyroid diagnosis: integrating AI-driven CAD framework with numerical data and ultrasound images [0.03%]
基于人工智能的CAD框架与数值数据和超声图像结合以促进甲状腺诊断的发展
Saleh Ateeq Almutairi
Saleh Ateeq Almutairi
This study proposes an advanced computer-aided diagnosis (CAD) framework for thyroid disease diagnosis that integrates numerical patient data and ultrasound images. The framework uses cutting edge technologies, including Vision Transformers...
A literature survey of shapelet quality measures for time series classification [0.03%]
时间序列分类中形似素质量测量方法的文献综述
Teng Li,Xiaodong Guo,Cun Ji
Teng Li
With the rapid development of the Internet of Things, time series classification (TSC) has gained significant attention from researchers due to its applications in various real-world fields, including electroencephalogram/electrocardiogram ...
Reem Alshareef,Mohammad Alshayeb,Mahmood Niazi et al.
Reem Alshareef et al.
Software maturity models can be utilized by organizations to evaluate and enhance their development processes. Established and recognized models such as the Capability Maturity Model Integrated (CMMI) and ISO/IEC 15504 (Software Process Imp...
Muhammad Sadiq Rohei,Kasturi Dewi Varathan,Shivakumara Palaiahnakote et al.
Muhammad Sadiq Rohei et al.
Depression is a rapidly increasing mental disorder that can interfere with a person's ability and negatively affect functions in various aspects of life. Fortunately, machine learning and deep learning techniques have demonstrated excellent...
Tracing truth: dynamic temporal networks for multi-modal fake news detection [0.03%]
追踪真理：多模态假新闻检测的动态时序网络
Jiaen Hu,Juan Zhang,Zichen Li
Jiaen Hu
As the internet continues to evolve rapidly and social media becomes increasingly prevalent, the ways people access information has become increasingly diverse. However, the proliferation of fake news has emerged as a critical problem, pres...
A hybrid deep learning approach with progressive cyclical CNN and firebug swarm optimization for breast cancer detection [0.03%]
一种用于乳腺癌检测的混合深度学习方法：逐步循环CNN和火龙果群优化算法
Sudha Prathyusha Jakkaladiki,Filip Malý
Sudha Prathyusha Jakkaladiki
The practice of diagnosing breast cancer retains its scope for improvement in medical imaging, where every correct and timely diagnosis enhances the survival rate of patients. This article presents an integrated approach utilizing patch-wis...
Transformer-based tokenization for IoT traffic classification across diverse network environments [0.03%]
基于变压器的物联网交通分类令牌化技术跨多种网络环境分析
Firdaus Afifi,Faiz Zaki,Hazim Hanif et al.
Firdaus Afifi et al.
The rapid expansion of the Internet of Things (IoT) has significantly increased the volume and diversity of network traffic, making accurate IoT traffic classification crucial for maintaining network security and efficiency. However, existi...
HMCFormer (hierarchical multi-scale convolutional transformer): a hybrid CNN+Transformer network for intelligent VIA screening [0.03%]
一种混合CNN+Transformer网络的智能VIA筛查方法(HMCFormer)
Bo Feng,Chao Xu,Zhengping Li et al.
Bo Feng et al.
Cervical cancer ranks first in incidence among malignant tumors of the female reproductive system, and 80% of women who die from cervical cancer worldwide are from developing countries. Visual inspection with acetic acid (VIA) screening bas...
HEMF: an adaptive hierarchical enhanced multi-attention feature fusion framework for cross-scale medical image classification [0.03%]
一种自适应分层增强多注意力特征融合框架用于跨尺度医学图像分类（HEMF）
Jingdong He,Qiang Shi,Jun Ma et al.
Jingdong He et al.
Medical image classification is essential for contemporary clinical diagnosis and decision support systems. However, medical images generally have similar inter-class features and complex structure patterns, making it a challenging task. Wh...
A progressive attention-based cross-modal fusion network for cardiovascular disease detection using synchronized electrocardiogram and phonocardiogram signals [0.03%]
一种基于渐进注意力的跨模态融合网络，用于心脏病的检测（使用同步心电图和心音图信号）
Wei Peng Li,Joon Huang Chuah,Guo Jeng Tan et al.
Wei Peng Li et al.
Synchronized electrocardiogram (ECG) and phonocardiogram (PCG) signals provide complementary diagnostic insights crucial for improving the accuracy of cardiovascular disease (CVD) detection. However, existing deep learning methods often uti...