Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...

Tiny particles bounce light around in a unique way, a property that researchers are using to detect pollutants in water and ...

Physical artificial intelligence (PAI) is the application of AI and machine learning (ML) algorithms to enable autonomous ...

When Hend Alqaderiwas studying how saliva could predict the risk of diabetes or the severity of a coronavirus infection, she collected a lot of saliva samples-thousands, measuring hundreds of bacteria ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

Abstract: Magnetic localization does not require line of sight, this makes it suitable for various applications, including indoor navigation, surgical tracking, motion capture, and 3D body scanning.

Abstract: This paper explores the application of reinforcement learning (RL) algorithms in optimizing personalized cognitive behavioral therapy (CBT) for anxiety disorders. Traditional CBT often lacks ...