Background: Coronary Artery Disease (CAD) is one of the biggest causes of mortality worldwide. Risk stratification for early detection is essential for the primary prevention of CAD. QRISK3 is known ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

Abstract: Motorcycle accidents are a global issue, often leading to severe injuries or fatalities due to delayed emergency responses. In response, RiderRescue introduces an innovative IoT-based crash ...

Researchers from MIT, Microsoft, and Google have introduced a “periodic table of machine learning” that stands to unify many different machine learning techniques using a single framework. Their ...

Katherine Bouman had a secret: An algorithm she'd developed had stitched together a picture of a black hole. She told nobody except her colleagues. Until last week. That's when Event Horizon Telescope ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...

A novel causal machine learning algorithm can determine which patients with atrial fibrillation (AFib) are more likely to benefit from left atrial appendage occlusion (LAAO) compared with ...