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What is Basal-Cell Carcinoma Detection Classifier about?

This document discusses the development of a cell-level classifier for detecting basal-cell carcinoma by integrating human visual attention maps with low-level handcrafted features. The proposed model, which combines various levels of image information, was validated using a dataset of 24 cases, achieving an accuracy of 74.49% in predicting cancer presence. The approach aims to enhance diagnostic accuracy in digital pathology by leveraging expert knowledge from pathologists

Author

Antonio Luis Sánchez Torres

Language

EN