Deep learning, a multifaceted and groundbreaking subset of Artificial Intelligence (AI), is reshaping various sectors, notably materials science. Its algorithms are now leveraged to predict and ...

A research team has developed a novel direct sampling method based on deep generative models. Their method enables efficient ...

Deep learning models had high sensitivity in screening for pulmonary hypertension and congenital heart disease–associated PAH.

Researchers at The University of Osaka have developed a computer graphics (CG) model, NeuraLeaf, capable of representing a ...

Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in ...

As the world grapples with climate change and dwindling fossil fuel reserves, biodiesel emerges as a promising renewable ...

A team of scientists at Georgia Southern University has combined both spatial and temporal attention mechanisms to develop a new approach for PV inverter fault detection. Training the new method on a ...

Medical image segmentation is one of the most important tasks in modern healthcare. Every pixel in a scan tells a story, whether it marks a healthy cell, a cancerous growth, or a vital organ boundary.

In order to improve the diagnostic accuracy of deep-learning AI algorithms, models require larger amounts of high-quality ...

In a new study, researchers from Mass General Brigham and their collaborators present Tripath: new, deep learning models that can use 3D pathology datasets to make clinical outcome predictions.