Pietro Strobbia

This study investigates augmentation strategies to improve protein language model performance by reducing dataset size and enhancing generalization through active learning and generative models.

This paper demonstrates a proof-of-concept model using machine learning and SERS to predict cancer from small extracellular vesicles, with explainable AI for interpretability.