Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Abstract: In the rapidly evolving landscape of smart grid cybersecurity, the integration of artificial intelligence and machine learning algorithms has emerged as a pivotal element in fortifying ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Researchers from MIT, Microsoft, and Google have introduced a “periodic table of machine learning” that stands to unify many different machine learning techniques using a single framework. Their ...

Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...

Abstract: Recent machine learning (ML) advances have opened up new possibilities for addressing various challenges. Given their ability to tackle complex problems, the use of ML algorithms in ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...