Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives
Artificial intelligence using deep learning has been applied to gastrointestinal disorders for the detection, classification, and delineation of various lesion images. With the accumulation of enormous medical records, the evolution of computation power with graphic processing units, and the widespr...
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| Format: | Article |
| Language: | English |
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Jin Publishing & Printing Co.
2020-03-01
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| Series: | The Korean Journal of Gastroenterology |
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| Online Access: | http://www.kjg.or.kr/journal/view.html?uid=5554&vmd=Full& |
| _version_ | 1819178274040840192 |
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| author | Chang Seok Bang |
| author_facet | Chang Seok Bang |
| author_sort | Chang Seok Bang |
| collection | DOAJ |
| description | Artificial intelligence using deep learning has been applied to gastrointestinal disorders for the detection, classification, and delineation of various lesion images. With the accumulation of enormous medical records, the evolution of computation power with graphic processing units, and the widespread use of open-source libraries in large-scale machine learning processes, medical artificial intelligence is overcoming its traditional limitations. This paper explains the basic concepts of deep learning model establishment and summarizes previous studies on upper gastrointestinal disorders. The limitations and perspectives on future development are also discussed. |
| first_indexed | 2024-12-22T21:39:56Z |
| format | Article |
| id | doaj.art-95425afb2c66489399b6ce2fc223e1f0 |
| institution | Directory Open Access Journal |
| issn | 1598-9992 2233-6869 |
| language | English |
| last_indexed | 2024-12-22T21:39:56Z |
| publishDate | 2020-03-01 |
| publisher | Jin Publishing & Printing Co. |
| record_format | Article |
| series | The Korean Journal of Gastroenterology |
| spelling | doaj.art-95425afb2c66489399b6ce2fc223e1f02022-12-21T18:11:38ZengJin Publishing & Printing Co.The Korean Journal of Gastroenterology1598-99922233-68692020-03-01753120131https://doi.org/10.4166/kjg.2020.75.3.120Deep Learning in Upper Gastrointestinal Disorders: Status and Future PerspectivesChang Seok Bang0https://orcid.org/0000-0003-4908-5431Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, KoreaArtificial intelligence using deep learning has been applied to gastrointestinal disorders for the detection, classification, and delineation of various lesion images. With the accumulation of enormous medical records, the evolution of computation power with graphic processing units, and the widespread use of open-source libraries in large-scale machine learning processes, medical artificial intelligence is overcoming its traditional limitations. This paper explains the basic concepts of deep learning model establishment and summarizes previous studies on upper gastrointestinal disorders. The limitations and perspectives on future development are also discussed.http://www.kjg.or.kr/journal/view.html?uid=5554&vmd=Full&artificial intelligenceneural networkscomputerdeep learninggastroenterologyendoscopy |
| spellingShingle | Chang Seok Bang Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives The Korean Journal of Gastroenterology artificial intelligence neural networks computer deep learning gastroenterology endoscopy |
| title | Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives |
| title_full | Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives |
| title_fullStr | Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives |
| title_full_unstemmed | Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives |
| title_short | Deep Learning in Upper Gastrointestinal Disorders: Status and Future Perspectives |
| title_sort | deep learning in upper gastrointestinal disorders status and future perspectives |
| topic | artificial intelligence neural networks computer deep learning gastroenterology endoscopy |
| url | http://www.kjg.or.kr/journal/view.html?uid=5554&vmd=Full& |
| work_keys_str_mv | AT changseokbang deeplearninginuppergastrointestinaldisordersstatusandfutureperspectives |