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

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry challenges like the "patent cliff" and high clinical failure rates. AI-driven ...

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 ...

Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...

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 ...

Their model used 1,557 epigenetic markers measured in blood. Using these markers, the researchers reported that they could assign people to high-risk prediabetes clusters with around 90 per cent ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

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