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Abstract Introduction: Quantitative nuclear morphology links cytopathological assessment with interpretable diagnostic modeling and provides a practical foundation for teaching medical artificial intelligence. This study evaluated a reproducible framework that connects nuclear feature interpretation, malignant-versus-benign classification, and evidence-based assessment of diagnostic decisions.
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