1 First Department of Dermatology, School of Medicine, Faculty of Health Sciences, Aristotle University, Thessaloniki, Greece
2 First Department of Dermatology, National and Kapodistrian University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
3 Second Department of Dermatology, School of Medicine, Faculty of Health Sciences, Aristotle University, Thessaloniki, Greece
4 Dermatology Unit, University of Campania L. Vanvitelli, Naples, Italy

Introduction

Multiple reader studies have shown that artificial intelligence (AI)- based analysis can classify images of benign and malignant skin tumors with an accuracy comparable, or superior to, human readers [1-3]. Although not tested in real-life clinical settings, automated classification has been incorporated in most available devices for total body photography (TBP) and digital dermoscopy (DD). This offers an opportunity for an initial assessment of its performance in a real-life clinical setting.

Case Presentation

We randomly examined the performance of automated AI classification of all photographed skin lesions in consecutive patients who underwent TBP and DD over a period of one week in September 2025. No patient was excluded from the analysis, regardless of the reason that justified the indication for TBP and DD.

To read the full article please click here.

The post Artificial Intelligence-Based Image Analysis is Insufficient as a Stand-Alone Assessment of Skin Tumors in Real Clinical Practice appeared first on MoleMax Systems.