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      Deep Learning and Its Applications in Biomedicine

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          Abstract

          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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          Most cited references104

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          The random subspace method for constructing decision forests

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            Methods of conjugate gradients for solving linear systems

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              Deep Learning in Neural Networks: An Overview

              (2014)
              In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarises relevant work, much of it from the previous millennium. Shallow and deep learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
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                Author and article information

                Contributors
                Journal
                Genomics Proteomics Bioinformatics
                Genomics Proteomics Bioinformatics
                Genomics, Proteomics & Bioinformatics
                Elsevier
                1672-0229
                2210-3244
                06 March 2018
                February 2018
                06 March 2018
                : 16
                : 1
                : 17-32
                Affiliations
                [1 ]CapitalBio Corporation, Beijing 102206, China
                [2 ]Department of Biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, China
                [3 ]State Key Lab of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 500040, China
                [4 ]Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 500040, China
                [5 ]Department of Biomedical Engineering, Medical Systems Biology Research Center, Tsinghua University School of Medicine, Beijing 100084, China
                Author notes
                [#]

                Equal contribution.

                [a]

                ORCID: 0000-0002-5262-6959.

                [b]

                ORCID: 0000-0001-9410-676X.

                [c]

                ORCID: 0000-0002-0616-5645.

                [d]

                ORCID: 0000-0001-5989-1635.

                [e]

                ORCID: 0000-0001-9044-2352.

                [f]

                ORCID:0000-0002-9003-7733.

                [g]

                ORCID: 0000-0001-7103-1814.

                [h]

                ORCID: 0000-0003-3490-5812.

                [i]

                ORCID: 0000-0002-5589-4836.

                Article
                S1672-0229(18)30002-0
                10.1016/j.gpb.2017.07.003
                6000200
                29522900
                96d3cf4d-bd9c-4dfb-a618-79eb4a8983ba
                © 2018 The Authors. Production and hosting by Elsevier B.V. on behalf of Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China.

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 18 June 2017
                : 5 July 2017
                Categories
                Review

                deep learning,big data,bioinformatics,biomedical informatics,medical image,high-throughput sequencing

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