Deep Learning and Its Applications in Biomedicine.
Deep Learning and Its Applications in Biomedicine.
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DOI：
10.1016/j.gpb.2017.07.003
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发表时间：
2018-03
期刊：
影响因子：
--
通讯作者：
Xie Z
中科院分区：
文献类型：
--
作者：
Cao C;Liu F;Tan H;Song D;Shu W;Li W;Zhou Y;Bo X;Xie Z
生物和医学技术的进步为我们提供了大量的生物和生理数据，如医学图像、脑电图、基因组和蛋白质序列。从这些数据中学习有助于了解人类健康和疾病。基于深度学习的算法从人工神经网络发展而来，在从复杂数据中提取特征和学习模式方面显示出巨大的前景。本文的目的是提供深度学习技术的概述和一些最先进的应用在生物医学领域。我们首先介绍人工神经网络和深度学习的发展。然后我们描述了深度学习的两个主要组成部分，即深度学习架构和模型优化。随后，展示了深度学习应用的一些例子，包括医学图像分类、基因组序列分析以及蛋白质结构分类和预测。最后，对深度学习领域的未来发展方向提出了展望。
Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field. We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization. Subsequently, some examples are demonstrated for deep learning applications, including medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. Finally, we offer our perspectives for the future directions in the field of deep learning.
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影响因子：
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作者：
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通讯作者：
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