Development and validation of the interpretability analysis system based on deep learning model for smart image follow-up of nail pigmentation.

ABSTRACT:

Background

Nail pigmentation can be a clinical manifestation of malignant melanoma and a variety of benign diseases. Nail matrix biopsy for pathologic examination, the gold standard for diagnosis of subungual melanoma, is a painful procedure and may result in nail damage. Therefore, there is a great need for non-invasive methods and long-term follow-up for nail pigmentation. The objective of this study is to establish an intelligent precursor system to provide convenient monitoring for nail pigmentation, early warning subungual melanoma, and reduce nail biopsies to the minimum necessary.

Methods

Dermoscopic images of nail lesions were obtained from outpatients between 2019 and 2020. The images were divided into the training set and the test set using k-fold cross validation

SUBMITTER: Chen Y 

PROVIDER: S-EPMC9201122 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature