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What is Predicting Skin Lesion Elevation for Diagnosis about?

This study investigates the prediction of skin lesion elevation from 2D images to enhance the diagnosis of skin lesions using deep learning models. The authors demonstrate that incorporating elevation labels as auxiliary inputs can improve classification performance, achieving AUROC improvements of up to 6.29% for dermoscopic images. The research highlights the potential of leveraging elevation information in teledermatology to aid in accurate diagnoses, especially in the absence of physical palpation.

Author

Lamiss Kara

Language

EN