Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, ...

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...

In a future perhaps not too far away, artificial intelligence and its subfield of machine learning (ML) tools and models, ...

A groundbreaking study led by USC Assistant Professor of Computer Science Ruishan Liu has uncovered how specific genetic mutations influence cancer treatment outcomes-insights that could help doctors ...

Machine learning is no longer just a tech buzzword. Businesses face constant pressure to stay competitive in an ever-changing digital environment. Many feel overwhelmed by the rapid pace of change and ...

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...

Please provide your email address to receive an email when new articles are posted on . The model, along with a traffic-light system, boosted sensitivity and specificity of agitation recognition.

Imagine having a super-powered lens that uncovers hidden secrets of ultra-thin materials used in our gadgets. Research led by University of Florida engineering professor Megan Butala enables a novel ...

A new machine learning tool called PhysMAP separates the electrical signatures of different cell types, offering a new way to study schizophrenia and depression.

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...