Abstract: A premature ventricular contraction (PVC) disrupt the normal heart rhythm and indicate underlying cardiac disease. We aim to detect these PVC beats from electrocardiogram (ECG/EKG) data by ...

Introduction: Acute coronary syndrome (ACS) is a life-threatening emergency, with occlusion myocardial infarction (OMI) requiring rapid diagnosis and treatment. The 12-lead ECG remains the primary ...

Abstract: Timely stroke detection is essential for effective treatment and improved patient outcomes. Traditional methods like MRI and CT scans, while informative, are often expensive and ...

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...

The Electrocardiogram Machine is a modern, health-focused web application designed to visualize electrocardiogram (ECG) data, which measures the heart’s electrical activity of the heart. Users can ...

The model is trained solely on ECG signals using HRV and EDR features with an LSTM-based neural network.

Microplastics have been found to be highly pervasive in the environment, driving concerns for health, environment, and ecology. Analytical methods that can accurately identify microplastics are ...

Novel targeted treatments increase the need for prompt hypertrophic cardiomyopathy (HCM) detection. However, its low prevalence (0.5%) and resemblance to common diseases present challenges that may ...