Medicine and Health

Prospective multicenter study using artificial intelligence to improve dermoscopic melanoma diagnosis in patient care

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This groundbreaking multicenter study conducted by the authors showcases the ADAE algorithm's impressive diagnostic accuracy for melanoma detection, outperforming dermatologists in balanced accuracy and sensitivity. The research, spanning eight hospitals and incorporating various camera setups, opens new avenues for AI in supporting dermatological practices, particularly in complex cases.

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Abstract

This prospective multicenter study assessed the diagnostic accuracy of the ADAE algorithm, an open-source ensemble algorithm, for melanoma detection. The study compared ADAE's performance to that of dermatologists on a heterogeneous test set from eight hospitals, using four different camera setups and including rare melanoma subtypes. ADAE demonstrated higher balanced accuracy and sensitivity than dermatologists, though with lower specificity. The results suggest AI could support dermatologists, particularly in diagnosing challenging cases.

Publisher

Nature Portfolio

Published On

Sep 11, 2024

Authors

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