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 ...

Researchers have developed a machine learning model capable of predicting whether a patient with depression will respond to ...

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

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 ...

ctDNA versus 18F-FDG PET-CT in predicting long-term disease control in patients with advanced melanoma undergoing immune checkpoint blockade therapy. Delineating the role of the microbiome and tumor ...

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

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

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

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

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