Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

ML is poised to become faster and more accessible by 2026. Simply having the support of GenAI already gives it an advantage over other AI-based solutions.

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 ...

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...

AI transforms digital wallets from transaction processors into intelligent systems. Instead of enforcing fixed rules, machine learning models evaluate context like user behavior, device ...

Professor Agathe Mezzadri-Guedj leads a session of NEOMA Business School’s required first-year literature course, where ...

Using machine learning, an electronic nose can "smell" early signs of ovarian cancer in the blood. The method is precise and, ...

While some industries have been slower to explore how they might use AI in their operations, the financial services sector ...

BIOPREVENT’ AI tool predicts transplant-related immune conflict and mortality risk using biomarkers, helping doctors ...

Vinay Sharma et Olga Fink, du Laboratoire IMOS, ont développé une IA capable de simuler des systèmes complexes tout en ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.