Robail Yasrab

This paper develops a multi-omics pipeline using MOFA and LLMs to classify breast cancer subtypes, achieving higher accuracy than traditional models.

The paper evaluates transformer models for binary semantic segmentation in CT scans, finding a redesigned Unet outperforms existing models with high precision and recall.

RootNav 2.0 uses deep learning to automatically extract root architectures from plant images, achieving comparable accuracy to semi-automatic methods with significantly increased speed.