Improving Artificial Intelligence-Based Diagnosis on Pediatric Skin Lesions.

ABSTRACT: Artificial intelligence algorithms to classify melanoma are dependent on their training data, which limits generalizability. The objective of this study was to compare the performance of an artificial intelligence model trained on a standard adult-predominant dermoscopic dataset before and after the addition of additional pediatric training images. The performances were compared using held-out adult and pediatric test sets of images. We trained two models: one (model A) on an adult-predominant dataset (37,662 images from the International Skin Imaging Collaboration) and the other (model A+P) on an additional 1,536 pediatric images. We compared performance between the two models on adult and pediatric held-out test images separately using the area under the receiver operating characteristic

SUBMITTER: Mehta PP 

PROVIDER: S-EPMC10431965 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature