The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Introduction: Acute coronary syndrome (ACS) is a life-threatening emergency, with occlusion myocardial infarction (OMI) requiring rapid diagnosis and treatment. The 12-lead ECG remains the primary ...

A personal repo for small ML projects I build while learning new algorithms — like simple linear regression and more. Nothing major here, just hands-on practice to apply what I’ve learned.

Abstract: This project focuses on utilizing machine learning techniques to identify and detect abnormal cardiac conditions through the analysis of Electrocardiogram (ECG) signals. With cardiovascular ...

Google Colab is a really handy tool for anyone working with machine learning and data stuff. It’s free, it runs in the cloud, and it lets you use Python without a lot of fuss. Whether you’re just ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Liver diseases present a significant global health challenge and often require costly, invasive ...

ECG-based machine learning offers a promising, interpretable approach for liver disease detection, particularly in resource-limited settings. By revealing clinically relevant biomarkers, this method ...

WaveformNet is a deep learning project for classifying electrocardiogram (ECG) signals into multiple arrhythmia types using convolutional neural networks. It features two separately trained models: a ...

Purpose: This study analyzed the research trends in machine learning (ML) pertaining to myocardial infarction (MI) from 2008 to 2024, aiming to identify emerging trends and hotspots in the field, ...