Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...

Structural economic models, while parsimonious and interpretable, often exhibit poor data fit and limited forecasting performance. Machine learning models, by contrast, offer substantial flexibility ...

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...

A collaborative approach to training AI models can yield better results, but it requires finding partners with data that ...

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, methicillin-resistant Staphylococcus aureus (MRSA) accounted for more than 100,000 global ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...

To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...

A team from the Faculty of Medicine and Health Sciences and the Institute of Neurosciences at the University of Barcelona ...