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A systematic review on application of deep learning in digestive system image processing
With the advent of the big data era, the application of artificial intelligence represented by deep learning in medicine has become a hot topic. In gastroenterology, deep learning has accomplished remarkable accomplishments in endoscopy, imageology, and pathology. Artificial intelligence has been ap...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557108/ https://www.ncbi.nlm.nih.gov/pubmed/34744231 http://dx.doi.org/10.1007/s00371-021-02322-z |
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author | Zhuang, Huangming Zhang, Jixiang Liao, Fei |
author_facet | Zhuang, Huangming Zhang, Jixiang Liao, Fei |
author_sort | Zhuang, Huangming |
collection | PubMed |
description | With the advent of the big data era, the application of artificial intelligence represented by deep learning in medicine has become a hot topic. In gastroenterology, deep learning has accomplished remarkable accomplishments in endoscopy, imageology, and pathology. Artificial intelligence has been applied to benign gastrointestinal tract lesions, early cancer, tumors, inflammatory bowel diseases, livers, pancreas, and other diseases. Computer-aided diagnosis significantly improve diagnostic accuracy and reduce physicians’ workload and provide a shred of evidence for clinical diagnosis and treatment. In the near future, artificial intelligence will have high application value in the field of medicine. This paper mainly summarizes the latest research on artificial intelligence in diagnosing and treating digestive system diseases and discussing artificial intelligence's future in digestive system diseases. We sincerely hope that our work can become a stepping stone for gastroenterologists and computer experts in artificial intelligence research and facilitate the application and development of computer-aided image processing technology in gastroenterology. |
format | Online Article Text |
id | pubmed-8557108 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-85571082021-11-01 A systematic review on application of deep learning in digestive system image processing Zhuang, Huangming Zhang, Jixiang Liao, Fei Vis Comput Survey With the advent of the big data era, the application of artificial intelligence represented by deep learning in medicine has become a hot topic. In gastroenterology, deep learning has accomplished remarkable accomplishments in endoscopy, imageology, and pathology. Artificial intelligence has been applied to benign gastrointestinal tract lesions, early cancer, tumors, inflammatory bowel diseases, livers, pancreas, and other diseases. Computer-aided diagnosis significantly improve diagnostic accuracy and reduce physicians’ workload and provide a shred of evidence for clinical diagnosis and treatment. In the near future, artificial intelligence will have high application value in the field of medicine. This paper mainly summarizes the latest research on artificial intelligence in diagnosing and treating digestive system diseases and discussing artificial intelligence's future in digestive system diseases. We sincerely hope that our work can become a stepping stone for gastroenterologists and computer experts in artificial intelligence research and facilitate the application and development of computer-aided image processing technology in gastroenterology. Springer Berlin Heidelberg 2021-10-31 2023 /pmc/articles/PMC8557108/ /pubmed/34744231 http://dx.doi.org/10.1007/s00371-021-02322-z Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Survey Zhuang, Huangming Zhang, Jixiang Liao, Fei A systematic review on application of deep learning in digestive system image processing |
title | A systematic review on application of deep learning in digestive system image processing |
title_full | A systematic review on application of deep learning in digestive system image processing |
title_fullStr | A systematic review on application of deep learning in digestive system image processing |
title_full_unstemmed | A systematic review on application of deep learning in digestive system image processing |
title_short | A systematic review on application of deep learning in digestive system image processing |
title_sort | systematic review on application of deep learning in digestive system image processing |
topic | Survey |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8557108/ https://www.ncbi.nlm.nih.gov/pubmed/34744231 http://dx.doi.org/10.1007/s00371-021-02322-z |
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