5,572 SMS messages. 747 spam. Can a custom neural network compete with BERT? This project compares three deep learning approaches to SMS spam detection: a custom LSTM architecture built from scratch, ...

Abstract: Past few years have seen increase in the number of spam emails and messages. Legal, economic and technical measures can be used to tackle spam sms's nowadays. A key role is being played by ...

Abstract: The number of people using mobile devices is increasing steadily. Both smartphones and low-end phones may use the text messaging service known as SMS (short message service). As a result, ...

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 ...

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex metabolic disorder and one of the leading causes of chronic liver disease worldwide. Current diagnostic tools, such as ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

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 ...