Artificial Intelligence-Based Image Analysis is Insufficient as a Stand-Alone Assessment of Skin Tumors in Real Clinical Practice

Aimilios Lallas; Konstantinos  Liopyris; Zoe  Apalla; Elvira  Moscarella; Gabriella  Brancaccio; Alexander  Stratigos; Giuseppe  Argenziano

doi:10.5826/dpc.1502a5353

Artificial Intelligence-Based Image Analysis is Insufficient as a Stand-Alone Assessment of Skin Tumors in Real Clinical Practice

Authors

Aimilios Lallas First Department of Dermatology, School of Medicine, Faculty of Health Sciences, Aristotle University, Thessaloniki, Greece
Konstantinos Liopyris First Department of Dermatology, National and Kapodistrian University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
Zoe Apalla Second Department of Dermatology, School of Medicine, Faculty of Health Sciences, Aristotle University, Thessaloniki, Greece
Elvira Moscarella Dermatology Unit, University of Campania L. Vanvitelli, Naples, Italy
Gabriella Brancaccio Dermatology Unit, University of Campania L. Vanvitelli, Naples, Italy
Alexander Stratigos First Department of Dermatology, National and Kapodistrian University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece
Giuseppe Argenziano Dermatology Unit, University of Campania L. Vanvitelli, Naples, Italy

Keywords:

Artificial Intelligence (AI), Skin tumors, Total body photography (TBP), Digital dermoscopy (DD), Diagnostic accuracy

References

Tschandl P, Codella N, Akay BN, et al. Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study. Lancet Oncol. 2019; 20(7): 938-947. DOI:10.1016/S1470-2045(19)30333-X.

Tschandl P, Rinner C, Apalla Z, et al. Human-computer collaboration for skin cancer recognition. Nat Med. 2020; 26(8): 1229-1234. DOI: 10.1038/s41591-020-0942-0.

Haggenmüller S, Maron RC, Hekler A, et al. Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts. Eur J Cancer. 2021; 156: 202-216. DOI: 10.1016/j.ejca.2021.06.049.

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Published

2025-04-30

Issue

Vol. 15 No. 2 (2025): 2025 Vol 15, No 2 | April

Section

Research Letter

License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Dermatology Practical & Conceptual applies a Creative Commons Attribution License (CCAL) to all works we publish (http://creativecommons.org/licenses/by-nc/4.0/). Authors retain the copyright for their published work.

How to Cite

Lallas A, Liopyris K, Apalla Z, et al. Artificial Intelligence-Based Image Analysis is Insufficient as a Stand-Alone Assessment of Skin Tumors in Real Clinical Practice. Dermatol Pract Concept. 2025;15(2):5353 . doi:10.5826/dpc.1502a5353