Last year, US banks used real-time machine learning to flag over 90 percent of suspected fraud, yet almost half of chargeback disputes were still managed manual ...

Threat actors are operationalizing AI to scale and sustain malicious activity, accelerating tradecraft and increasing risk for defenders, as illustrated by recent activity from North Korean groups ...

AI is reshaping online search in ways that reduce friction for consumers while increasing it for businesses. Large language ...

Image courtesy by QUE.com The University of North Texas (UNT) is stepping into the future with a new undergraduate major in ...

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

Let's discuss why AI-powered data management is becoming essential in industrial automation and how organizations can build it successfully.

Abstract: Effective disaster prediction is essential for disaster management and mitigation. This study addresses a multi-classification problem and proposes the Neural-XGBoost disaster prediction ...

The University of North Texas (UNT) is stepping into the future with a new undergraduate major in Artificial Intelligence (AI), ...

Snowflake performance within the NYSE Composite highlights quarterly earnings results, cloud data platform expansion, institutional activity, and competitive dynamics across enterprise analytics ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...

Text-based depression estimation using natural language processing has emerged as a feasible approach for early mental health screening. However, most existing reviews often included studies with weak ...

Abstract: This study explores a machine learning approach for detecting and classifying fetal health which is a crucial aspect in ensuring proper care and wellbeing of both fetus and the mother. The ...