Machine learning (ML) is reshaping pipeline integrity management (PIM) from physics-based to data-driven paradigms. This ...

AI is already boosting positive outcomes in health care and holds promise for delivering many more. It is important, however, that deployment of AI tools—especially in a life-or-death health care ...

Read more about Banks could strengthen credit card fraud screening with ensemble machine learning model on Devdiscourse ...

Learn what machine learning is, how it works, its types, the algorithms it uses, and its real-world uses in this complete ...

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...

Blood‐based biomarkers for stroke subtyping could improve triage in emergency settings. We used cross‐platform proteomics to identify plasma biomarkers differentiating major stroke diagnostic groups.

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 ...

Abstract: Reducing energy consumption has become a pressing need for modern machine learning, which has achieved many of its most impressive results by scaling to larger and more energy-consumptive ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

Abstract: Heart attacks are a prominent source of morbidity and mortality globally, demanding the development of precise and efficient predictive models for early identification and risk ...