Official implementation of our IEEE:SMC 2021 paper "IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification"

Myocardial Infarction Detection

Classifier for detection and prediction of the type of MI or NORM from 12-lead ECG beats.

MyoPS-Net: Myocardial Pathology Segmentation with Flexible Combination of Multi-Sequence CMR images

MS and LVEF classification for ECG image using multi-task deep learning. Demo website (in Thai) ↓

Use of segmentation models to extract the epicardium in low-quality echocardiograms. Dataset used: https://www.kaggle.com/datasets/aysendegerli/hmcqu-dataset

Bachelor Thesis in Biomedical Engineering about Myocardial Ischemia Detection Using DWT Feature Extraction and Artificial Neural Networks Classifier

Statistical data analysis of the myocardial infarction for life or death prognosis using PCA method

single cell experiments in STEMI participants

Repository contains my MATLAB files for the hand-coded Myocardial-Infarction detection model trained on EKG data whose features were carefully engineered for the EEL5813 - Neural Networks: Algorithms and Applications course, PROJECT03

Membuat model yang dapat melakukan deteksi rekaman suara myocardial infarction

Spatial transcriptomics of cardiac tissue 24 h after ischemic injury

This project focuses on the detection of myocardial infarction (heart attack) using machine learning techniques. We leverage the PTB diagnostic database, a widely used dataset in the field of cardiology.

Graph Neural Networks for Mycardial Infarction Prediction

Hyaluronan Mediated Motility Receptor (Hmmr) overexpression