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 ...

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

More than half of transplant recipients in a large analysis developed chronic graft-versus-host disease, and 15% died from causes other than cancer relapse. Those numbers capture the uneasy truth of ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

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