Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

The global artificial intelligence (AI) in drug discovery market is experiencing rapid expansion, driven by the need to reduce the high costs and long timelines of traditional pharmaceutical ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Users can note which content they would like to view more frequently. Instagram is handing users some control in deciding what content they see. The social media giant is allowing users to have a say ...

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 ...

Abstract: We introduce a fully unsupervised framework designed to reconstruct X-ray CT images from truncated projections without requiring prior truncation correction. By incorporating a Radon ...

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 ...

ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...

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 ...

An image depicting the integration of AI technologies in banking, showcasing how legacy banks can evolve with AI advancements for improved customer experiences and operational efficiency. Supervised ...