A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges
Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …
and has recently received significant interest as a promising biometric trait. However, ECG …
An overview on state-of-the-art electrocardiogram signal processing methods: Traditional to AI-based approaches
Over the last decade, cardiovascular diseases (CVD's) are the leading cause of death
globally. Early prediction of CVD's can help in reducing the complications of high-risk …
globally. Early prediction of CVD's can help in reducing the complications of high-risk …
A novel approach for brain tumour detection using deep learning based technique
Identifying the tumour's extent is a major challenge in planning treatment for brain tumours
and correctly measuring their size. Magnetic resonance imaging (MRI) has emerged as a …
and correctly measuring their size. Magnetic resonance imaging (MRI) has emerged as a …
An efficient ECG arrhythmia classification method based on Manta ray foraging optimization
The Electrocardiogram (ECG) arrhythmia classification has become an interesting research
area for researchers and developers as it plays a vital role in early prevention and diagnosis …
area for researchers and developers as it plays a vital role in early prevention and diagnosis …
An automatic arrhythmia classification model based on improved marine predators algorithm and convolutions neural networks
Abstract Preparation of Convolutional Neural Networks (CNNs) for classification purposes
depends heavily on the knowledge of hyper-parameters tuning. This study aims, in particular …
depends heavily on the knowledge of hyper-parameters tuning. This study aims, in particular …
BAED: A secured biometric authentication system using ECG signal based on deep learning techniques
Biometric authentication technology has become increasingly common in our daily lives as
information protection and control regulation requirements have grown worldwide. A …
information protection and control regulation requirements have grown worldwide. A …
Wavelet transform and vector machines as emerging tools for computational medicine
V Gupta - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
Electrocardiogram (ECG) is a most primitive and important test to analyse the status of the
heart functioning. During this test, different types of noises and artefacts get involved in the …
heart functioning. During this test, different types of noises and artefacts get involved in the …
[HTML][HTML] Application of Kronecker convolutions in deep learning technique for automated detection of kidney stones with coronal CT images
Kidney stone disease is a serious public health concern that is getting worse with changes
in diet, obesity, medical conditions, certain supplements etc. A kidney stone also called a …
in diet, obesity, medical conditions, certain supplements etc. A kidney stone also called a …
Ecg heartbeat classification using machine learning and metaheuristic optimization for smart healthcare systems
Early diagnosis and classification of arrhythmia from an electrocardiogram (ECG) plays a
significant role in smart healthcare systems for the health monitoring of individuals with …
significant role in smart healthcare systems for the health monitoring of individuals with …
SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
Abstract Background and Objective The global population has been heavily impacted by the
COVID-19 pandemic of coronavirus. Infections are spreading quickly around the world, and …
COVID-19 pandemic of coronavirus. Infections are spreading quickly around the world, and …