Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Advances in ultrasound—the same imaging technology that uses sound waves to allow doctors to monitor babies in utero—are being applied by engineers at the University of California San Diego to make ...

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 ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

AI is searching particle colliders for the unexpected ...

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 ...