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Application of artificial intelligence in pancreaticobiliary diseases
The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890713/ https://www.ncbi.nlm.nih.gov/pubmed/33644756 http://dx.doi.org/10.1177/2631774521993059 |
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author | Goyal, Hemant Mann, Rupinder Gandhi, Zainab Perisetti, Abhilash Zhang, Zhongheng Sharma, Neil Saligram, Shreyas Inamdar, Sumant Tharian, Benjamin |
author_facet | Goyal, Hemant Mann, Rupinder Gandhi, Zainab Perisetti, Abhilash Zhang, Zhongheng Sharma, Neil Saligram, Shreyas Inamdar, Sumant Tharian, Benjamin |
author_sort | Goyal, Hemant |
collection | PubMed |
description | The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system. |
format | Online Article Text |
id | pubmed-7890713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-78907132021-02-26 Application of artificial intelligence in pancreaticobiliary diseases Goyal, Hemant Mann, Rupinder Gandhi, Zainab Perisetti, Abhilash Zhang, Zhongheng Sharma, Neil Saligram, Shreyas Inamdar, Sumant Tharian, Benjamin Ther Adv Gastrointest Endosc Artificial Intelligence in gastrointestinal endoscopy The role of artificial intelligence and its applications has been increasing at a rapid pace in the field of gastroenterology. The application of artificial intelligence in gastroenterology ranges from colon cancer screening and characterization of dysplastic and neoplastic polyps to the endoscopic ultrasonographic evaluation of pancreatic diseases. Artificial intelligence has been found to be useful in the evaluation and enhancement of the quality measure for endoscopic retrograde cholangiopancreatography. Similarly, artificial intelligence techniques like artificial neural networks and faster region-based convolution network are showing promising results in early and accurate diagnosis of pancreatic cancer and its differentiation from chronic pancreatitis. Other artificial intelligence techniques like radiomics-based computer-aided diagnosis systems could help to differentiate between various types of cystic pancreatic lesions. Artificial intelligence and computer-aided systems also showing promising results in the diagnosis of cholangiocarcinoma and the prediction of choledocholithiasis. In this review, we discuss the role of artificial intelligence in establishing diagnosis, prognosis, predicting response to treatment, and guiding therapeutics in the pancreaticobiliary system. SAGE Publications 2021-02-15 /pmc/articles/PMC7890713/ /pubmed/33644756 http://dx.doi.org/10.1177/2631774521993059 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Artificial Intelligence in gastrointestinal endoscopy Goyal, Hemant Mann, Rupinder Gandhi, Zainab Perisetti, Abhilash Zhang, Zhongheng Sharma, Neil Saligram, Shreyas Inamdar, Sumant Tharian, Benjamin Application of artificial intelligence in pancreaticobiliary diseases |
title | Application of artificial intelligence in pancreaticobiliary diseases |
title_full | Application of artificial intelligence in pancreaticobiliary diseases |
title_fullStr | Application of artificial intelligence in pancreaticobiliary diseases |
title_full_unstemmed | Application of artificial intelligence in pancreaticobiliary diseases |
title_short | Application of artificial intelligence in pancreaticobiliary diseases |
title_sort | application of artificial intelligence in pancreaticobiliary diseases |
topic | Artificial Intelligence in gastrointestinal endoscopy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890713/ https://www.ncbi.nlm.nih.gov/pubmed/33644756 http://dx.doi.org/10.1177/2631774521993059 |
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