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

作者信息

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

机构信息

First Department of Dermatology, School of Medicine, Faculty of Health Sciences, Aristotle University, Thessaloniki, Greece.

First Department of Dermatology, National and Kapodistrian University of Athens School of Medicine, Andreas Sygros Hospital, Athens, Greece.

出版信息

Dermatol Pract Concept. 2025 Apr 1;15(2):5353. doi: 10.5826/dpc.1502a5353.

DOI:10.5826/dpc.1502a5353
PMID:40401873
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12090926/
Abstract
摘要

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Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.基于卷积神经网络的皮肤癌分类：涉及人类专家的研究的系统综述。
Eur J Cancer. 2021 Oct;156:202-216. doi: 10.1016/j.ejca.2021.06.049. Epub 2021 Sep 8.
2
Human-computer collaboration for skin cancer recognition.人机协作进行皮肤癌识别。
Nat Med. 2020 Aug;26(8):1229-1234. doi: 10.1038/s41591-020-0942-0. Epub 2020 Jun 22.
3
Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.比较人类读者和机器学习算法在色素性皮肤病变分类中的准确性：一项开放的、基于网络的、国际性的、诊断性研究。
Lancet Oncol. 2019 Jul;20(7):938-947. doi: 10.1016/S1470-2045(19)30333-X. Epub 2019 Jun 12.