JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches |
| 영문제목(English Title) |
Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches |
| 저자(Author) |
Ning Yu
Zeng Yu
Feng Gu
Tianrui Li
Xinmin Tian
Yi Pan
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| 원문수록처(Citation) |
VOL 13 NO. 02 PP. 0204 ~ 0214 (2017. 04) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
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.
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| 키워드(Keyword) |
Bioinformatics
Deep Learning
Deep Neural Network
DNA Genome Analysis
Image Data Analysis
Machine Learning
lincRNA
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| 파일첨부 |
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