IEEE

Analysis of spam detection techniques using machine learning

Abstract: In recent years, the receipt of spam by billions of users around the world has increased. In general, for spam emails are admitted all emails that is sent without the express consent of the ...
IEEE

Enhancing Machine Learning Algorithms for Imbalanced Data—A Case Study: Spam Detection

Abstract: Nowadays, emails are among the most common and cost-effective ways to share and exchange information. However, because of their simplicity, they are highly vulnerable to various threats. In ...
GitHub

sohayb-elbakali/spam-detection

This project implements an end-to-end spam detection system leveraging Apache Spark's distributed computing capabilities for scalable machine learning. The system processes text messages through a ...
GitHub

Machine Learning spam classifier achieving 98% accuracy using SVM, NLP, and TF-IDF vectorization

An intelligent spam detection system that classifies SMS/email messages with 98.48% accuracy using machine learning. This project compares multiple algorithms and provides comprehensive performance ...
The American Journal of Managed Care

Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
ahajournals.org

Abstract Fri013: AI-Driven Gait Classification for Peripheral Artery Disease (PAD) Detection Using Machine Learning and Nonlinear Gait Dynamics

Introduction: Peripheral Artery Disease (PAD) is a progressive vascular disorder impairing mobility, raising fall risk, and reducing quality of life. Early detection is key to preventing amputations ...
Albert Lea Tribune

Learning about Spam

Look for Progress 2011: Everyday Heroes in the Sunday, Feb. 27 edition of the Albert Lea Tribune. Read about dozens of inspirational stories about interesting community members, leaders in faith, ...