Mar 10, 2018

Deep Learning and Its Applications in Biomedicine

Genomics, Proteomics & Bioinformatics
Chensi CaoZhi Xie

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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Mentioned in this Paper

Biological Neural Networks
Patterns
Classification
Electroencephalography
Genome
Gene Products, Protein
Biomedical Engineering Field
Image Interpretation, Computer-Assisted
Neural Network Simulation
Genomics

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