Explainable Segmentation-Guided Mamba-Transformer Framework for Automated Cardiovascular Disease Detection

Key Points

• This research aims to improve the accuracy of cardiovascular disease detection using automated methods.
• Developed an explainable segmentation-guided framework
• Utilized a Mamba-Transformer architecture
• Applied to cardiac images for enhanced diagnosis
• Demonstrated improved diagnostic accuracy for cardiovascular diseases
• Utilized deep learning techniques effectively