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1
Circulating biomarkers predictive of tumor response to cancer immunotherapy.循环生物标志物预测癌症免疫治疗的肿瘤反应。
Expert Rev Mol Diagn. 2019 Oct;19(10):895-904. doi: 10.1080/14737159.2019.1659728. Epub 2019 Sep 10.
2
Embracing machine learning and digital health technology for precision dermatology.拥抱机器学习和数字健康技术以实现精准皮肤科。
J Dermatolog Treat. 2020 Aug;31(5):494-495. doi: 10.1080/09546634.2019.1623373. Epub 2019 Jun 14.
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Machine Learning in Medicine.医学中的机器学习
N Engl J Med. 2019 Apr 4;380(14):1347-1358. doi: 10.1056/NEJMra1814259.
4
Artificial intelligence in dermatology: are we there yet?皮肤科中的人工智能：我们做到了吗？
Br J Dermatol. 2019 Jul;181(1):190-191. doi: 10.1111/bjd.17899.
5
A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task.在一项临床黑色素瘤图像分类任务中，经过皮肤镜图像训练的卷积神经网络在性能上可与 145 名皮肤科医生相媲美。
Eur J Cancer. 2019 Apr;111:148-154. doi: 10.1016/j.ejca.2019.02.005. Epub 2019 Mar 8.
6
Automated detection of nonmelanoma skin cancer using digital images: a systematic review.使用数字图像自动检测非黑色素瘤皮肤癌：一项系统综述。
BMC Med Imaging. 2019 Feb 28;19(1):21. doi: 10.1186/s12880-019-0307-7.
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Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark.将人工智能算法与 157 名德国皮肤科医生进行比较：黑素瘤分类基准。
Eur J Cancer. 2019 Apr;111:30-37. doi: 10.1016/j.ejca.2018.12.016. Epub 2019 Feb 22.
8
Can clinical decision making be enhanced by artificial intelligence?人工智能能否增强临床决策能力？
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Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.基于词嵌入的机器学习方法在免疫介导性皮肤病药物再利用预测中的应用。
J Invest Dermatol. 2019 Mar;139(3):683-691. doi: 10.1016/j.jid.2018.09.018. Epub 2018 Oct 17.
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Diagnostic accuracy of content-based dermatoscopic image retrieval with deep classification features.基于深度学习分类特征的基于内容的皮肤镜图像检索的诊断准确性。
Br J Dermatol. 2019 Jul;181(1):155-165. doi: 10.1111/bjd.17189. Epub 2018 Oct 17.

Machine learning for precision dermatology: Advances, opportunities, and outlook.

作者信息

Lee Ernest Y, Maloney Nolan J, Cheng Kyle, Bach Daniel Q

机构信息

Department of Bioengineering, University of California-Los Angeles; Division of Dermatology, Department of Medicine, University of California-Los Angeles; University of California-Los Angeles-Caltech Medical Scientist Training Program, David Geffen School of Medicine at University of California-Los Angeles.

Division of Dermatology, Department of Medicine, University of California-Los Angeles.

出版信息

J Am Acad Dermatol. 2021 May;84(5):1458-1459. doi: 10.1016/j.jaad.2020.06.1019. Epub 2020 Jul 6.

DOI:10.1016/j.jaad.2020.06.1019
PMID:32645400
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8023050/
Abstract
摘要