A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Researchers develop a radiomics-based machine learning model to identify patients with traumatic brain injury at risk ...

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits and suddenly, a molecule makes a promising new medicine. Normally, creating better ...

A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

MIT researchers introduce a technique that improves how AI systems explain their predictions, helping users assess trust in critical applications like healthcare and autonomous driving.

LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...

Statistical insights into machine learning analysis can help researchers evaluate model performance and may even provide new physical understanding.

New book explains how AI and machine learning are transforming banking through fraud detection, credit risk modeling, ...

What’s the first thing you think of when you hear about ai security threats and vulnerabilities? If you’re like most people, your mind probably jumps to Large Language Model (LLM) ...