EurekAlert!

AI analyzes brainwaves to unlock movement in spinal cord injury cases

This paper proposes a deep learning framework F-GCN that integrates multiple wavelet bases, and extracts MI brain electrical ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...
Scientific Research Publishing

Advanced Skin Disease Diagnosis and Treatment: Leveraging Convolutional Neural Networks for Image-Based Prediction and Comprehensive Health Assistance ()

Skin conditions are a worldwide health issue that requires prompt and accurate diagnosis in order to be effectively treated. This study presents a Convolutional Neural Network (CNN)-based automated ...
IEEE

Cutting-Edge Convolutional Neural Network Autoencoders for Anomaly Detection in ECG Signals: Advancements in Early Cardiac Diagnosis

Abstract: The current research deals with the complex domain of ECG signal processing and classification using convolutional neural network auto-encoders. Much attention was placed on the PTB ...
Frontiers

Erratum: Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups

Due to a production error, the first sentence of the Results paragraph in the abstract was incorrectly given as “The CNN based on single-lead ECG (D1) outperformed the one based on the standard ...
ahajournals.org

Convolution Neural Network Algorithm for Shockable Arrhythmia Classification Within a Digitally Connected Automated External Defibrillator

Diagnosis of shockable rhythms leading to defibrillation remains integral to improving out‐of‐hospital cardiac arrest outcomes. New machine learning techniques have emerged to diagnose arrhythmias on ...
IEEE

Convolutional Neural Networks for patient-specific ECG classification

Abstract: We propose a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system using an adaptive implementation of 1D Convolutional Neural Networks (CNNs) that ...