Abstract: Deep learning models have the potential to improve the accuracy and speed of medical microwave imaging. However, their performance often suffers due to a lack of high-quality data.

Abstract: Decision tree boosting algorithms, such as XGBoost, have demonstrated superior predictive performance on tabular data for supervised learning compared to neural networks. However, recent ...