Deep learning (DL) has been introduced in automatic heart-abnormality classification using
ECG signals, while its application in practical medical procedures is limited. A systematic …

This study introduces a sophisticated neural network structure for segmenting breast tumors.
It achieves this by combining a pretrained Vision Transformer (ViT) model with a UNet …

Cardiovascular disorders are known to be among the most severe diseases and the leading
causes of mortality all over the globe. Premature ventricular contractions (PVC) are one of …

Cardiovascular Diseases (CVDs) have become a burden to the healthcare system due to
the increase in the number of patients and the ratio of mortality. Various techniques are …

Automatic detection of premature ventricular contractions (PVCs) is essential for early
identification of cardiovascular abnormalities and reduction of clinical workload. As the most …

The real-time and accurate detection of premature ventricular contractions (PVC) in patients
is of great significance for preventing the occurrence of high-risk events such as sudden …

This research presents a novel methodology for classifying MRI images into two categories:
tumor and non-tumor. The study utilizes a combination of two advanced Convolutional …

Purpose The development of an automated premature ventricular contraction (PVC)
detection system has significant implications for early intervention and treatment decisions …

The signal under consideration is a biologically significant indicator utilized to diagnose
heart disorders, as it exhibits the cyclic contraction and relaxation patterns of the myocardial …

O eletrocardiograma (ECG) é um método não invasivo que ajuda a identificar sintomas de
doenças do coração que podem levar à morte. É um gráfico que registra as flutuações da …