Abstract: Revealing the latent low-dimensional geometric structure of high-dimensional data is a crucial task in unsupervised representation learning. Traditional manifold learning, as a typical ...

Introduction: Myocardial ischemia can result in severe cardiovascular complications. However, the impact of clinical factors on myocardial ischemia in individuals with T2DM remains unclear. we applied ...

Department of Chemistry, Zhongshan Hospital, Fudan University, Shanghai 200000, China Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200092 ...

Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...

Got a stair lift you no longer need? Whether you’re moving, your mobility has improved or you’re preparing to sell your home, removing a stair lift presents a daunting challenge. The heavy equipment, ...

Abstract: Federated Learning (FL) has emerged as a foundational paradigm that enables collaborative training of deep neural networks across distributed clients while ensuring data privacy. However, ...

Artificial intelligence research is rapidly evolving beyond pattern recognition and toward systems capable of complex, human-like reasoning. The latest breakthrough in this pursuit comes from the ...

Summary: New research reveals that the brain may be learning even during unstructured, aimless exploration. By recording activity in tens of thousands of neurons, scientists found that the visual ...

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...