Hybrid CNN–GCN framework for brain tumor MRI classification: A graph‐based approach to smart healthcare diagnostics

The integration of CNN-based hierarchical feature extraction with GCN-based relational reasoning provides a significant advancement in automated brain tumor classification. This reproducible and intelligent diagnostic pipeline demonstrates strong potential for clinical translation by enhancing diagnostic precision, reducing radiologist workload, and facilitating timely therapeutic interventions. The findings support the integration of graph-based deep learning systems into smart healthcare ecosystems, where AI-assisted diagnostic tools can contribute to improved outcomes in neuro-oncology.