The U.S. Army created a new AI and machine learning officer career field, launching initial selections through VTIP in 2026.

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 ...

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.

Abstract: To improve the accuracy of breast cancer diagnosis and reduce examination costs, a novel ensemble learning method called support vector dynamic learning neural network (SVDL) is proposed in ...

Background: Extremely aggressive prostate cancer, including subtypes like small cell carcinoma and neuroendocrine carcinoma, is associated with poor prognosis and limited treatment options. This study ...

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 ...

Abstract: In recent years, Federated Learning applied to neural networks has garnered significant attention, yet applying this approach to other machine learning algorithms remains underexplored.

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 ...