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 ...

This repository includes the code of the ECG-DualNet for ECG classification proposed in the paper Exploring Novel Algorithms for Atrial Fibrillation Detection by Driving Graduate Level Education in ...

This repository presents an automated machine learning approach in Python to create a stress monitoring system with data from devices such as fitness trackers. With the rising popularity of trackers ...

Subtle, prognostically important ECG features may not be apparent to physicians. In the course of supervised machine learning, thousands of ECG features are identified. These are not limited to ...

With the Sabarimala pilgrimage set to begin shortly, Cardiology at Doorstep (CAD) Foundation, floated by a group of health professionals in Mangaluru, donated two ECG machines to ‘Devotee Doctors of ...

Why it matters: In the global race for high-performance-computing dominance, Japan has positioned itself as a leader with its plans to build a zeta-class supercomputer. If it manages to achieve this ...

Abstract: Electrocardiogram (ECG) data’s high dimensionality challenges real-time arrhythmia classification. Our approach employs functional approximation to condense ECG recordings into a compact ...

Abstract: This paper presents an explainable, low-complexity binary electrocardiogram (ECG) classifier to be deployed in a resource-limited wearable edge device. The presented technique could be used ...

Markets Insider and Business Insider Editorial Teams were not involved in the creation of this post. Indices Commodities Currencies Stocks ...