Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Abstract: This study proposes a machine learning based methodology for estimating Arctic thin sea ice thickness (up to 1 m) from brightness temperature measurements of SMOS. The approach involves ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in ...

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 ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its ...

A research team has developed a new way to measure and predict how plant leaves scatter and reflect light, revealing that ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses the kernel matrix inverse (Cholesky ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...