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 ...

AI may spot deadly heart risk in a routine ECG

UC Berkeley researchers trained AI to detect hidden warning signs of sudden cardiac death in routine ECG tests, according to ...
The Lancet

Forecasting left ventricular systolic dysfunction in heart failure with artificial intelligence

aDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA bResearch Laboratory for Electronics, Massachusetts Institute of Technology ...
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

Channel-Imposed Fusion: A Simple yet Effective Method for Medical Time Series Classification

A simple model with good features beats a complex model with poor features. Medical time series (MedTS), such as EEG and ECG, are critical for clinical diagnosis but face two main challenges: generic ...
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 ...
Frontiers

AI-based preeclampsia detection and prediction with electrocardiogram data

More than 76,000 women die yearly from preeclampsia and hypertensive disorders of pregnancy. Early diagnosis and management of preeclampsia can improve outcomes for both mother and baby. In this study ...