MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

The inversion of the one-dimensional wave spectrum from dual-polarized synthetic aperture radar (SAR) data is performed using machine learning methods, namely Random Forest (RF), eXtreme Gradient ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Researchers analyzed clinical data and RNA expression from the peripheral blood of 174 patients with gout and hyperuricemia that had been collected at week 48 of their participation in the STOP Gout ...

Abstract: In the era of large-scale machine learning, large-scale clusters are extensively used for data processing jobs. However, the state-of-the-art heuristic-based and Deep Reinforcement Learning ...

As AI becomes more common and decisions more data-driven, a new(ish) form of information is on the rise: synthetic data. And some proponents say it promises more privacy and other vital benefits. Data ...

As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...

Please provide your email address to receive an email when new articles are posted on . Familial hypercholesterolemia is underdiagnosed and undertreated. A novel machine learning algorithm identified ...

Nvidia’s (NASDAQ: NVDA) stock price has taken a hit, retreating from its recent high above $180. However, artificial intelligence (AI) tools are projecting that the equity will likely reclaim this ...