Deep Learning and Its Applications in Biomedicine
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...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2018-02-01
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| Series: | Genomics, Proteomics & Bioinformatics |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1672022918300020 |
| _version_ | 1797368203227168768 |
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| author | Chensi Cao Feng Liu Hai Tan Deshou Song Wenjie Shu Weizhong Li Yiming Zhou Xiaochen Bo Zhi Xie |
| author_facet | Chensi Cao Feng Liu Hai Tan Deshou Song Wenjie Shu Weizhong Li Yiming Zhou Xiaochen Bo Zhi Xie |
| author_sort | Chensi Cao |
| collection | DOAJ |
| description | 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. Keywords: Deep learning, Big data, Bioinformatics, Biomedical informatics, Medical image, High-throughput sequencing |
| first_indexed | 2024-03-08T17:29:16Z |
| format | Article |
| id | doaj.art-f39538e8327345219d9feb75d33d2ddd |
| institution | Directory Open Access Journal |
| issn | 1672-0229 |
| language | English |
| last_indexed | 2024-03-08T17:29:16Z |
| publishDate | 2018-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Genomics, Proteomics & Bioinformatics |
| spelling | doaj.art-f39538e8327345219d9feb75d33d2ddd2024-01-02T17:13:30ZengElsevierGenomics, Proteomics & Bioinformatics1672-02292018-02-011611732Deep Learning and Its Applications in BiomedicineChensi Cao0Feng Liu1Hai Tan2Deshou Song3Wenjie Shu4Weizhong Li5Yiming Zhou6Xiaochen Bo7Zhi Xie8CapitalBio Corporation, Beijing 102206, ChinaDepartment of Biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, ChinaState Key Lab of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 500040, ChinaState Key Lab of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 500040, ChinaDepartment of Biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, ChinaZhongshan School of Medicine, Sun Yat-sen University, Guangzhou 500040, ChinaCapitalBio Corporation, Beijing 102206, China; Department of Biomedical Engineering, Medical Systems Biology Research Center, Tsinghua University School of Medicine, Beijing 100084, China; Corresponding authors.Department of Biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, China; Corresponding authors.State Key Lab of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 500040, China; Corresponding authors.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. Keywords: Deep learning, Big data, Bioinformatics, Biomedical informatics, Medical image, High-throughput sequencinghttp://www.sciencedirect.com/science/article/pii/S1672022918300020 |
| spellingShingle | Chensi Cao Feng Liu Hai Tan Deshou Song Wenjie Shu Weizhong Li Yiming Zhou Xiaochen Bo Zhi Xie Deep Learning and Its Applications in Biomedicine Genomics, Proteomics & Bioinformatics |
| title | Deep Learning and Its Applications in Biomedicine |
| title_full | Deep Learning and Its Applications in Biomedicine |
| title_fullStr | Deep Learning and Its Applications in Biomedicine |
| title_full_unstemmed | Deep Learning and Its Applications in Biomedicine |
| title_short | Deep Learning and Its Applications in Biomedicine |
| title_sort | deep learning and its applications in biomedicine |
| url | http://www.sciencedirect.com/science/article/pii/S1672022918300020 |
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