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Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches
Yu, Ning,Yu, Zeng,Gu, Feng,Li, Tianrui,Tian, Xinmin,Pan, Yi Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.2
Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.
Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches
( Ning Yu ),( Zeng Yu ),( Feng Gu ),( Tianrui Li ),( Xinmin Tian ),( Yi Pan ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.2
Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.