Evaluation of thermal stresses in the blast furnace hearth with consideration of refractory block contact

Abstract

The accurate classification of brain pathologies is critical for early diagnosis,treatment  planning, and improving patient outcomes. Traditional diagnostic methods, while effective, often suffer from limitations in precision, speed, and consistency. In this study, we propose an improved hybrid deep learning strategy that integrates convolutional neural networks (CNNs) with transformer-based architectures to enhance the classification of brain abnormalities from medical imaging data such as MRI and CT scans.