rabiul-ai Goto Github PK

arrhythmia_classification

CNN, Attention and Transformer based Hybrid Model for ECG Arrhythmia Classification

camus_challenge

This repository hosts all the code and information related to CAMUS challenge.

cnn-imi

This is a repository for the code developed to produced the results in the paper "Detection of Inferior Myocardial Infarction using Shallow Convolutional Neural Networks" (https://arxiv.org/abs/1710.01115v3)

dl-ecg-review

A Review of Deep Learning Methods on ECG Data

dpc-msgatnet

dynamic

EchoNet-Dynamic is a deep learning model for assessing cardiac function in echocardiogram videos.

ecg-classification

Code for training and evaluating CNNs to classify ECG signals from the MIT-BIH arrhythmia database.

echocardiography-assess

etab

A Benchmark Suite for Visual Representation Learning in Echocardiography

graph-machine-learning

Graph Machine Learning, published by Packt

lungnoduledetectionclassification

Automated Extraction and Classification of Pulmonary Lung Nodules from CT Scans

matplotlib_tutorial

Source code to go along with my tutorial to learn data visualization with the matplotlib library of Python

medical-imaging-datasets

A list of Medical imaging datasets.

mit-bih_ecg_recognition

MIT-BIH ECG data recognition using 1d CNN with tensorflow2

mnist-digit-classification

This code can classify 10 handwritten digit by simple neural network using Pytorch

opencv

Open Source Computer Vision Library

opencv-course

Learn OpenCV in 4 Hours - Code used in my Python and OpenCV course on freeCodeCamp.

openface

Face recognition with deep neural networks.

pandas

Data & Code for my video on the Pandas library of Python

pytorchtutorial

PyTorch Tutorials from my YouTube channel

rabiul-ai

Config files for my GitHub profile.

realtimearrhythmiamonitoring

repo1

Firstly testing to create a repo

tmed2-echocardiogram-classifiers

Code for classification of echocardiograms (view type, severity level) with the TMED dataset

zero-shot-ecg

A Personalized Zero-Shot ECG Anomaly Monitoring System: From Sparse Representation Based Domain Adaption to Energy Efficient Suspicious Beat Detection for a Practical ECG Surveillance