Abstract: Data stream learning is an emerging machine learning paradigm designed for environments where data arrive continuously and must be processed in real time. Unlike traditional batch learning, ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Data Science Program, University of Delaware, Newark, Delaware 19716, United States Department of Materials Science and Engineering, University of Delaware, Newark, Delaware 19716, United States ...

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 ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

Abstract: This paper presents a dynamic selector model for data workload prediction. A main function responsible for selecting the most accurate Machine Learning Algorithm (e.g., Linear Regression, ...

In the past few years, HR has seen a significant transformation driven by the rise of machine learning tools and technology. 1 These tools extract insights, patterns, and predict trends from massive ...

1 Espace Dev, Université de Perpignan Via Domitia, Perpignan, France 2 UMR Espace Dev (228), Université Montpellier, IRD, Montpellier, France Endurance-trained athletes require physiological ...

Introduction: Adverse drug events (ADEs) pose a significant challenge in current clinical practice. Machine learning (ML) has been increasingly used to predict specific ADEs using electronic health ...