Improving Diagnostic Sensitivity in Imbalanced Oral Cancer Image Classification: A Comparative Study of CNN and Transformer Architectures.
Researchers compared three machine-learning architectures on 3,000 oral images to classify lesions as healthy, benign, potentially malignant, or cancerous, finding that data augmentation improved cancer detection sensitivity and overall diagnostic performance better than under- or over-sampling approaches.
A plain-English summary of the study's own findings — we don't add our own claims or interpretation. Read the full paper for the complete methods and results, and apply your own clinical judgement.
Read the full study at the sourceRelated CPD from Vital Pulp
Managing the Pregnant Dental Patient
Confident, evidence-based dental care from the first trimester to the postpartum period
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