Researchers developed an AI model to detect myocardial ischemia and coronary microvascular and vasomotor dysfunction using ...

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality globally. Effective management ...

Mount Sinai analysis looks at the effectiveness of electrocardiograms analyzed via deep learning as a tool for early COPD detection ...

Brief Summary of the Effects of Cocaine on Cardiac Conduction Given the pervasiveness of cocaine use in communities and within hospitals, physicians practicing in emergency departments (EDs), medical ...

While EEG research might help you figure out extrasensory perception, we won’t be betting on it. However, if you want to read ...

It is a truth universally acknowledged that a man in possession of a good e-ink display, must be in want of a weather station ...

Priyanka Sharma is a health journalist with over 11 years of field reporting experience. She covers the union ministry of health and family welfare and department of pharmaceuticals for the ...

This repository implements ECG time-series anomaly detection using a reconstruction-based approach with an LSTM autoencoder in PyTorch. The objective is to model normal ECG dynamics and identify ...

A deep learning project for multilabel classification of ECG signals using Parallel xLSTM architecture. This project classifies ECG recordings into five cardiac conditions: Normal (NORM), Myocardial ...

Abstract: Convolutional Neural Networks (CNNs) have become a dominant solution for Electrocardiogram (ECG) beat classification, owing to their superior feature extraction capabilities. However, ...

Abstract: This paper presents a useful technique for totally automatic detection of myocardial infarction from patients' ECGs. Due to the large number of heartbeats constituting an ECG and the high ...