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Artificial Intelligence in Skin Diseases: Fulfilling its Potentials to Meet the Real Needs in Dermatology Practice.人工智能在皮肤病学中的应用：发挥其潜力以满足皮肤科实践中的实际需求。
Health Data Sci. 2022 Aug 8;2022:9791467. doi: 10.34133/2022/9791467. eCollection 2022.
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Improving skin cancer management with ARTificial intelligence: A pre-post intervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a real-world specialist dermatology setting.利用人工智能改善皮肤癌管理：一项在真实世界专科皮肤科环境中，将人工智能系统用作皮肤癌管理诊断辅助工具的干预前后试验。
J Am Acad Dermatol. 2023 May;88(5):1138-1142. doi: 10.1016/j.jaad.2022.10.038. Epub 2022 Oct 25.
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The role of artificial intelligence in cosmetic dermatology-Current, upcoming, and future trends.人工智能在美容皮肤科中的作用——当前、即将出现的及未来趋势。
J Cosmet Dermatol. 2021 Jan;20(1):48-52. doi: 10.1111/jocd.13797. Epub 2020 Nov 5.
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Response to Felmingham C. et al's "Improving Skin cancer Management with ARTificial intelligence (SMARTI): A pre-post intervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a real-world specialist dermatology setting".对费明厄姆C等人所著的《利用人工智能改善皮肤癌管理（SMARTI）：在现实世界专科皮肤科环境中用作皮肤癌管理诊断辅助工具的人工智能系统的干预前后试验》的回应
J Am Acad Dermatol. 2023 Aug;89(2):e107. doi: 10.1016/j.jaad.2023.03.062. Epub 2023 Apr 28.
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Toward Augmented Intelligence: The First Prospective, Randomized Clinical Trial Assessing Clinician and Artificial Intelligence Collaboration in Dermatology.迈向增强智能：首个评估皮肤科医生与人工智能协作的前瞻性、随机临床试验。
J Invest Dermatol. 2022 Sep;142(9):2301-2302. doi: 10.1016/j.jid.2022.03.019. Epub 2022 May 31.
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Improving Skin cancer Management with ARTificial Intelligence (SMARTI): protocol for a preintervention/postintervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a specialist dermatology setting.利用人工智能改善皮肤癌管理（SMARTI）：一项在专科皮肤科环境中使用人工智能系统作为皮肤癌管理诊断辅助工具的干预前/干预后试验方案。
BMJ Open. 2022 Jan 4;12(1):e050203. doi: 10.1136/bmjopen-2021-050203.
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Artificial Intelligence in Dermatology-Where We Are and the Way to the Future: A Review.人工智能在皮肤科领域的应用——现状与未来展望：综述。
Am J Clin Dermatol. 2020 Feb;21(1):41-47. doi: 10.1007/s40257-019-00462-6.
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Artificial intelligence in dermatology and healthcare: An overview.人工智能在皮肤病学和医疗保健中的应用：概述。
Indian J Dermatol Venereol Leprol. 2021;87(4):457-467. doi: 10.25259/IJDVL_518_19.
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Artificial intelligence in dermatology for the clinician.皮肤科临床医师的人工智能应用。
Clin Dermatol. 2021 Jul-Aug;39(4):667-672. doi: 10.1016/j.clindermatol.2021.03.012. Epub 2021 Mar 19.
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Perceptions of Artificial Intelligence Integration into Dermatology Clinical Practice: A Cross-Sectional Survey Study.人工智能融入皮肤科临床实践的认知：一项横断面调查研究。
J Drugs Dermatol. 2022 Feb 1;21(2):135-140. doi: 10.36849/jdd.6398.
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Robust QRS detection based on simulated degenerate optical parametric oscillator-assisted neural network.基于模拟简并光学参量振荡器辅助神经网络的稳健QRS波检测
Heliyon. 2024 Mar 30;10(7):e28903. doi: 10.1016/j.heliyon.2024.e28903. eCollection 2024 Apr 15.
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Skin Cancer Pathobiology at a Glance: A Focus on Imaging Techniques and Their Potential for Improved Diagnosis and Surveillance in Clinical Cohorts.皮肤癌病理生物学速览：聚焦影像学技术及其在临床队列中改善诊断和监测的潜力。
Int J Mol Sci. 2023 Jan 5;24(2):1079. doi: 10.3390/ijms24021079.
本文引用的文献
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Temporal Trends in the Incidence and Mortality of Skin Malignant Melanoma in China from 1990 to 2019.1990年至2019年中国皮肤恶性黑色素瘤发病率和死亡率的时间趋势
J Oncol. 2021 Aug 24;2021:9989824. doi: 10.1155/2021/9989824. eCollection 2021.
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Burden of melanoma in China, 1990-2017: Findings from the 2017 global burden of disease study.中国 1990-2017 年黑色素瘤负担：2017 年全球疾病负担研究的结果。
Int J Cancer. 2020 Aug 1;147(3):692-701. doi: 10.1002/ijc.32764. Epub 2019 Nov 21.
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Do no harm: a roadmap for responsible machine learning for health care.《医疗保健负责任机器学习的路线图：不造成伤害》。
Nat Med. 2019 Sep;25(9):1337-1340. doi: 10.1038/s41591-019-0548-6. Epub 2019 Aug 19.
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Dermatologist-level classification of skin cancer with deep neural networks.基于深度神经网络的皮肤癌皮肤科医生级分类。
Nature. 2017 Feb 2;542(7639):115-118. doi: 10.1038/nature21056. Epub 2017 Jan 25.
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