Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images.

ABSTRACT:

Background

Computer vision may aid in melanoma detection.

Objective

We sought to compare melanoma diagnostic accuracy of computer algorithms to dermatologists using dermoscopic images.

Methods

We conducted a cross-sectional study using 100 randomly selected dermoscopic images (50 melanomas, 44 nevi, and 6 lentigines) from an international computer vision melanoma challenge dataset (n = 379), along with individual algorithm results from 25 teams. We used 5 methods (nonlearned and machine learning) to combine individual automated predictions into "fusion" algorithms. In a companion study, 8 dermatologists classified the lesions in the 100 images as either benign or malignant.

Results

The average sensitivity and specificity of dermatologists in classification was

SUBMITTER: Marchetti MA 

PROVIDER: S-EPMC5768444 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature