Automated Oral Cancer Detection Using Hybrid CNNs for Enhanced Clinical Applications

This study introduces a hybrid, multimodal Convolutional Neural Network (CNN) model designed to automate oral cancer detection with high sensitivity and specificity. The model exhibits adaptability across diverse clinical environments, ensuring improved diagnostic outcomes regardless of variations in patient demographics or imaging modalities. Experimental evaluations highlight its potential for early diagnosis, making it a valuable tool for clinical practice.. Keywords - Hybrid CNN, Oral Cancer Detection, Deep Learning, Clinical Adaptability, Diagnostic Accuracy.