Scientists Want to Use AI to Track Elusive Particles in the World’s Most Powerful Collider

Muons are a key subatomic particle in the discovery of new physics, but after particle collision, they’re difficult to track.
Assembly Magazine

Machine Learning Detects Fastening Errors

Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...
Game Rant

One Piece Is Expanding Devil Fruit Classes With Nerona Imu's Akuma no Mi

Rei Penber is the Deputy Lead Editor for GameRant's Anime and Manga team, originally from Kashmir and currently based in Beirut. He brings seven years of professional experience as a writer and editor ...
Devdiscourse

AI exposes what ESG misses: Hidden risks in corporate financial reporting

A new study has found that artificial intelligence (AI) is uncovering deeper financial irregularities within firms, but the ...
IEEE

A Novel Relative Density and Nonmembership-Based Intuitionistic Fuzzy Twin SVM for Class Imbalance Learning

Abstract: A major challenge in machine learning is the accurate categorization of data in the presence of noise, outliers, and imbalanced class distributions. Fuzzy support vector machines and their ...
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...
Scientific Research Publishing

Erfani, S.M., Rajasegarar, S., Karunasekera, S. and Leckie, C. (2016) High-Dimensional and Large-Scale Anomaly Detection Using a Linear One-Class SVM with Deep Learning ...

ABSTRACT: Industrial appearance anomaly detection (AD) focuses on accurately identifying and locating abnormal regions in images. However, due to issues such as scarce abnormal samples, complex ...
Scientific Research Publishing

Machine Learning-Based Classification of Coronary Heart Disease: A Comparative Analysis of Logistic Regression, Random Forest, and Support Vector Machine Models ()

1 Department of Business Information System, Central Michigan University, Mount Pleasant, MI, USA. 2 Department of MPH, Central Michigan University, Mount Pleasant, MI, USA. 3 Department of ...
ahajournals.org

Abstract 172: A Machine Learning Model for Prediction of Short‐Term Functional Outcomes in Cerebral Venous Thrombosis

Dural Sinus and Cerebral Vein Thrombosis (CVT) represents a rare yet significant cause of stroke, with distinct pathophysiological mechanisms compared to arterial strokes. Despite the progress in ...