Multimodal hybrid mamba classification model for tumor pathological grade prediction using magnetic resonance images

Key Points

• Tumor pathological grades are efficiently classified using a multimodal hybrid model, improving diagnostic performance.
• The classification model achieves an impressive accuracy rate of 85% based on MRI analysis of tumor images.
• Analysis based on magnetic resonance images provides critical insights into tumor characteristics for grading.
• The findings suggest that advanced classification techniques can significantly enhance tumor classification efforts in clinical settings.