%0 Journal Article
%A Chanda, Tirtha
%A Haggenmueller, Sarah
%A Bucher, Tabea
%A Holland-Letz, Tim
%A Kittler, Harald
%A Tschandl, Philipp
%A Heppt, Markus V
%A Berking, Carola
%A Utikal, Jochen
%A Schilling, Bastian
%A Buerger, Claudia
%A Navarrete-Dechent, Cristian
%A Goebeler, Matthias
%A Kather, Jakob Nikolas
%A Schneider, Carolin V
%A Durani, Benjamin
%A Durani, Hendrike
%A Jansen, Martin
%A Wacker, Juliane
%A Wacker, Joerg
%A Brinker, Titus
%T Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study.
%J Nature Communications
%V 16
%N 1
%@ 2041-1723
%C [London]
%I Springer Nature
%M DKFZ-2025-01121
%P 4739
%D 2025
%Z #EA:C140#LA:C140#
%X Artificial intelligence (AI) systems substantially improve dermatologists' diagnostic accuracy for melanoma, with explainable AI (XAI) systems further enhancing their confidence and trust in AI-driven decisions. Despite these advancements, there remains a critical need for objective evaluation of how dermatologists engage with both AI and XAI tools. In this study, 76 dermatologists participate in a reader study, diagnosing 16 dermoscopic images of melanomas and nevi using an XAI system that provides detailed, domain-specific explanations, while eye-tracking technology assesses their interactions. Diagnostic performance is compared with that of a standard AI system lacking explanatory features. Here we show that XAI significantly improves dermatologists' diagnostic balanced accuracy by 2.8 percentage points compared to standard AI. Moreover, diagnostic disagreements with AI/XAI systems and complex lesions are associated with elevated cognitive load, as evidenced by increased ocular fixations. These insights have significant implications for the design of AI/XAI tools for visual tasks in dermatology and the broader development of XAI in medical diagnostics.
%K Melanoma: diagnosis
%K Melanoma: diagnostic imaging
%K Humans
%K Artificial Intelligence
%K Eye-Tracking Technology
%K Dermatologists
%K Skin Neoplasms: diagnosis
%K Skin Neoplasms: diagnostic imaging
%K Female
%K Dermoscopy: methods
%K Male
%K Nevus: diagnosis
%K Nevus: diagnostic imaging
%K Adult
%K Middle Aged
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:40399272
%2 pmc:PMC12095463
%R 10.1038/s41467-025-59532-5
%U https://inrepo02.dkfz.de/record/301729