Electrocardiography (ECG) is a crucial tool for diagnosing cardiovascular diseases. In
particular, combining clinical ECG with computer technology for automatic ECG analysis can …

Time series classification (TSC) is essential in various application domains to understand
the system dynamics. The adoption of deep learning has advanced TSC, however its …

This study compares the Accuracy of Support Vector Machine (SVM) Classifier and Decision
Tree (DT) Classifier in predicting Innovative Bradycardia disease diagnosis. Materials and …

We develop a machine learning (ML) model using electrocardiography (ECG) to predict
myocardial blood flow reserve (MFR) and assess its prognostic value for major adverse …

This review offers a detailed examination of modern ECG signal processing techniques
employed in the prediction and detection of ventricular fibrillation (VF). It contains a thorough …

Cardiovascular disorders are typically diagnosed using an Electrocardiogram (ECG). It is a
painless method that mimics the cyclical contraction and relaxation of the heart's muscles …

Abstract Background and Objective Left ventricular hypertrophy (LVH) can impair ejection
function and elevate the risk of heart failure. Therefore, early detection through screening is …

AI techniques have recently been put under the spotlight for analyzing electrocardiograms
(ECGs). However, the performance of AI-based models relies on the accumulation of large …

Segmentation an advancement of object detection where bounding boxes are placed
around object in object detection whereas segmentation is used to classify every pixel in the …

Nanotechnology seems to be an important scientific method for the diagnosis of a disorder
that offers more precise and appropriate health information. Diabetes mellitus (DM) is a …