AI cyberattacks are rapidly transforming the cybersecurity landscape, enabling attackers to automate and scale operations with unprecedented speed. Through machine learning hacking, adversaries can ...

This project implements an end-to-end deep learning pipeline for automated heartbeat classification using the MIT-BIH Arrhythmia Dataset. The system performs ECG signal preprocessing, heartbeat ...

Abstract: Early and accurate diagnosis of cardiac arrhythmias is essential for preventing potentially fatal cardiovascular events. Traditional ECG interpretation is often ineffective for continuous ...

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 ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as the Framingham ...

Introduction: Deep learning (DL) has proved effective for automatic identification of atrial fibrillation (AF) using single-lead ECG. Adoption and trust of DL by clinicians is limited by its black box ...

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 ...