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Does AI need anything more than a single image to diagnose melanoma?

作者信息

Lallas Aimilios, Paoli John

机构信息

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

Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

出版信息

J Eur Acad Dermatol Venereol. 2025 Aug;39(8):1378-1379. doi: 10.1111/jdv.20793.

DOI:10.1111/jdv.20793
PMID:40709547
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12290991/
Abstract
摘要

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本文引用的文献

1
Artificial Intelligence-Based Image Analysis is Insufficient as a Stand-Alone Assessment of Skin Tumors in Real Clinical Practice.在实际临床实践中，基于人工智能的图像分析作为皮肤肿瘤的独立评估方法并不充分。
Dermatol Pract Concept. 2025 Apr 1;15(2):5353. doi: 10.5826/dpc.1502a5353.
2
Effect of patient-contextual skin images in human- and artificial intelligence-based diagnosis of melanoma: Results from the 2020 SIIM-ISIC melanoma classification challenge.患者背景皮肤图像在基于人类和人工智能的黑色素瘤诊断中的作用：2020年SIIM-ISIC黑色素瘤分类挑战赛的结果
J Eur Acad Dermatol Venereol. 2024 Dec 8. doi: 10.1111/jdv.20479.
3
Prediction of melanoma metastasis using dermatoscopy deep features: an international multicentre cohort study.
Br J Dermatol. 2024 Oct 17;191(5):847-848. doi: 10.1093/bjd/ljae281.
4
A systematic review and meta-analysis of artificial intelligence versus clinicians for skin cancer diagnosis.人工智能与临床医生用于皮肤癌诊断的系统评价和荟萃分析。
NPJ Digit Med. 2024 May 14;7(1):125. doi: 10.1038/s41746-024-01103-x.
5
Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge.基于皮肤镜图像的皮肤癌诊断人工智能预测模型验证：2019 年国际皮肤成像协作挑战赛。
Lancet Digit Health. 2022 May;4(5):e330-e339. doi: 10.1016/S2589-7500(22)00021-8.
6
Dermoscopy of patients with multiple nevi: Improved management recommendations using a comparative diagnostic approach.多发性痣患者的皮肤镜检查：采用比较诊断方法改进管理建议
Arch Dermatol. 2011 Jan;147(1):46-9. doi: 10.1001/archdermatol.2010.389.