Malicious PyPI packages give hackers control of Telegram bot servers

A campaign active since last November has been targeting Python developers building Telegram bots with trojanized Pyrogram ...
Frontiers

Disease classification via interpretable machine learning based on multi-center routine coagulation test

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 ...
GitHub

ECG-DualNet: Atrial Fibrillation Classification in Electrocardiography using Deep Learning

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 ...
GitHub

Stress classifier with AutoML

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 ...
ahajournals.org

Prognostic Significance and Associations of Neural Network–Derived Electrocardiographic Features

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 ...
The Lancet

Demographic reporting in biosignal datasets: a comprehensive analysis of the PhysioNet open access database

aDepartment of Biomedical Engineering, Duke University, Durham, NC, USA bDepartment of Computer Science, Duke University, Durham, NC, USA cDepartment of Biostatistics & Bioinformatics, Duke University ...
Frontiers

WaSP-ECG: A Wave Segmentation Pretraining Toolkit for Electrocardiogram Analysis

Representation learning allows artificial intelligence (AI) models to learn useful features from large, unlabelled datasets. This can reduce the need for labelled data across a range of downstream ...
ahajournals.org

Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation–Related Stroke

Atrial fibrillation (AF) is associated with substantial morbidity, especially when it goes undetected. If new-onset AF could be predicted, targeted screening could be used to find it early. We ...