Cracking the code: How a 'prediction machine' is resurrecting the Singapore Stone

Several years ago, my linguistic research team and I began developing a computational tool we call "Read-y Grammarian." Our ...
EurekAlert!

Smart monitoring for a greener future: New AI-driven model predicts lithium-ion battery health with unprecedented accuracy

An accurate assessment of the state of health (SOH) is the cornerstone for guaranteeing the long-term stable operation of ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
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 ...
Medscape

Machine Learning Algorithm Predicts Gout Flares Using RNA

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...
news.bloomberglaw

Navigating a Patent Gap for AI and Machine Learning Algorithms

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...
Live Science

'Quantum AI' algorithms already outpace the fastest supercomputers, study says

Researchers have successfully demonstrated quantum speedup in kernel-based machine learning. When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works.
IEEE

Support Vector Machine Algorithm in Machine Learning

Abstract: The Support Vector methods was proposed by V.Vapnik in 1965, when he was trying to solve problems in pattern recognition. In 1971, Kimeldorf proposed a method of constructing kernel space ...
Assembly Mag

Traditional Machine Learning for Practical Machine Vision: It’s Been There All Along

Powerful and practical machine learning tools for machine vision applications are already available to everyone, even if you’re not a data scientist. It might come as a bit of a surprise, but machine ...
Scientific Research Publishing

A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites ()

The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by security ...