IEEE

Benchmarking Machine Learning Algorithms for Bearing Fault Classification Using Vibration Data: A Deployment-Oriented Study

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Frontiers

Explaining factors influencing students' depression with a deep learning approach

Objective: Student mental health has emerged as an increasingly prominent issue in sustainable educational healthcare systems. Accurately and promptly identifying students' depression and analyzing ...
IEEE

Optimizing Currency Classification and Counterfeit Detection with Machine Learning Algorithms

Abstract: Currency classification and counterfeit detection are crucial for protecting financial security and combating fraud. Traditional detection methods often rely on manual checks or ...
Frontiers

Medical pattern classification using a novel binary similarity approach based on an associative classifier

Classification is a central task in machine learning, underpinning applications in domains such as finance, medicine, engineering, information technology, and biology. However, machine learning ...