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 ...

This study aims to establish an interpretable disease classification model via machine learning and identify key features related to the disease to assist clinical disease diagnosis based on a ...

Abstract: A Non-stationary signal called an electrocardiogram (ECG) is utilized to evaluate the rate of cardiac beats. Doctors can identify Abstract - Heart Rate Variations (HRV) is one of the major ...

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 ...

An AI-powered web application for predicting and monitoring heart disease using a hybrid Transformer–CNN deep learning model. The system allows patients, clinicians, and administrators to interact ...

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 ...

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...

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 ...