Mattessich Sarah, Tassavor Michael, Swetter Susan M, Grant-Kels Jane M
University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Department of Dermatology, University of Connecticut School of Medicine, Farmington, Connecticut, USA.
Clin Dermatol. 2018 Nov-Dec;36(6):777-778. doi: 10.1016/j.clindermatol.2018.06.003. Epub 2018 Jun 8.
Artificial intelligence and its machine learning (ML) capabilities are very promising technologies for dermatology and other visually oriented fields due to their power in pattern recognition. Understandably, many physicians distrust replacing clinical finesse with unsupervised computer programs. We describe convolutional neural networks and discuss how this method of ML will impact the field of dermatology. ML is a form of artificial intelligence well suited for pattern recognition in visual applications. Many dermatologists are wary of such unsupervised algorithms and their future implications.
由于人工智能及其机器学习（ML）在模式识别方面的强大能力，它们对于皮肤科及其他视觉导向领域来说是非常有前景的技术。可以理解的是，许多医生不信任用无监督的计算机程序取代临床技巧。我们描述了卷积神经网络，并讨论这种机器学习方法将如何影响皮肤科领域。机器学习是人工智能的一种形式，非常适合视觉应用中的模式识别。许多皮肤科医生对这种无监督算法及其未来影响持谨慎态度。
