Nature

Data augmentation alters feature importance in XGBoost for CVD prediction

Machine learning models are powerful tools for cardiovascular disease (CVD) prediction, but their performance is often limited by dataset size and class imbalance. While data augmentation techniques ...
Nature

Self-supervised learning for data augmentation in histopathology image segmentation

In recent years, computational pathology has undergone an unprecedented development process due to novel trends in digital imaging technologies and deep learning mechanisms 1. The analysis of ...