With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

Machine learning (ML) is rapidly emerging as a powerful tool to improve the safety, reliability, and long-term performance of marine structures exposed to harsh ocean environments. This study presents ...

AMD’s next-generation Zen 6 CPU architecture has quietly made its first appearance through an internal developer document, ...

Researchers at National University of Singapore used multiple interpretable machine learning methods to predict traffic congestion in in Alameda ...

The IMF develops a machine-learning nowcasting framework to estimate quarterly non-oil GDP in GCC countries in real time, addressing long data lags and oil-driven distortions in headline GDP. By ...

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Ms. Mutcherson is a professor at Rutgers Law School. Right now in an Atlanta hospital room lies a 30-year-old nurse and mother, Adriana Smith. Ms. Smith, who is brain-dead, has been connected to life ...

ABSTRACT: Background and Theoretical Dilemma: The United States of America (USA) is the world’s largest consumer of crude oil in the world. Ensuring the sustainability of the role of crude oil in the ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...