In this study, an automated method for lumen, vessel wall, and plaque segmentation for quantitative assessment based on MR ...

A research team, led by Professor Jimin Lee and Professor Eisung Yoon in the Department of Nuclear Engineering at UNIST, has unveiled a deep learning–based approach that significantly ...

Researchers introduce RhoFold+, a groundbreaking deep learning model that predicts RNA 3D structures with unprecedented accuracy and efficiency, addressing critical challenges in structural biology.

1. Evolution of protein structure prediction methods: from traditional template-based modeling and template-free modeling approaches to the application of modern deep learning models such as ...

The third model combined both radiomics and deep learning but, with an AUC of 0.829 (CI, 0.797 to 0.862) and a PPV of 0.254 (CI, 0.228 to 0.281) at a sensitivity of 0.780 (CI, 0.721 to 0.840), did not ...

Quantifying treatment response to gastroesophageal junction (GEJ) adenocarcinomas is crucial to provide an optimal therapeutic strategy. Routinely taken tissue samples provide an opportunity to ...

Microsoft Research has introduced BioEmu-1, a deep-learning model designed to predict the range of structural conformations that proteins can adopt. Unlike traditional methods that provide a single st ...

One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as ...