Meijering Erik
School of Computer Science and Engineering & Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Australia.
Comput Struct Biotechnol J. 2020 Aug 7;18:2312-2325. doi: 10.1016/j.csbj.2020.08.003. eCollection 2020.
Deep learning of artificial neural networks has become the de facto standard approach to solving data analysis problems in virtually all fields of science and engineering. Also in biology and medicine, deep learning technologies are fundamentally transforming how we acquire, process, analyze, and interpret data, with potentially far-reaching consequences for healthcare. In this mini-review, we take a bird's-eye view at the past, present, and future developments of deep learning, starting from science at large, to biomedical imaging, and bioimage analysis in particular.
人工神经网络的深度学习已成为解决几乎所有科学和工程领域数据分析问题的事实上的标准方法。在生物学和医学领域，深度学习技术也正在从根本上改变我们获取、处理、分析和解释数据的方式，对医疗保健可能产生深远影响。在这篇小型综述中，我们从宏观科学开始，到生物医学成像，特别是生物图像分析，对深度学习的过去、现在和未来发展进行了鸟瞰。
