Artificial Intelligence in Gastrointestinal Disease: Diagnosis and Management
Gastrointestinal disease (GID), the disease of the gastrointestinal tract, is one of the main contributors to disease burden around the world. GID causes 8 million deaths around the world per year and cost 120 billion dollars in the United States in 2018 alone. Simultaneously, the notion of artifici...
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| Język: | angielski |
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MDPI - Multidisciplinary Digital Publishing Institute
2024
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| Dostęp online: | ONIX_20240514_9783725806539_420 |
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| description | Gastrointestinal disease (GID), the disease of the gastrointestinal tract, is one of the main contributors to disease burden around the world. GID causes 8 million deaths around the world per year and cost 120 billion dollars in the United States in 2018 alone. Simultaneously, the notion of artificial intelligence (AI) has gained great attention on a global level. Machine learning, a branch of AI extracting knowledge from large amounts of data, includes several common approaches, and a popular machine learning approach is the use of an artificial neural network (ANN), a group of neurons (information units) that are networked based on weights. An ANN normally has one input layer, one, two or three intermediate layers, and one output layer. A deep neural network (or deep learning) is an artificial neural network with a large number of intermediate layers, e.g., 5, 10 or even 1000. This Special Issue demonstrates the effectiveness and popularity of deep learning as a cutting-edge approach to the diagnosis and management of GID. This Special Issue covers a wide range of important topics including the classification, detection and segmentation of acute diverticulitis, colorectal cancer, gastric cancer, fatty liver, fecal material, inflammatory bowel disease, living-donor liver transplantation, neuroendocrine tumor and pancreatic cystic lesions. The Special Issue addresses the utility of explainable AI and large language models as well. In conclusion, this reprint will serve as an indispensable collection of original studies on the AI-based diagnosis and management of GID. |
| format | Online |
| id | doab-20.500.12854ir-137824 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1378242024-05-14T14:35:54Z Artificial Intelligence in Gastrointestinal Disease: Diagnosis and Management Kim, Eun-Sun Lee, Kwang-Sig deep learning transfer learning poorly differentiated adenocarcinoma colon machine learning artificial intelligence acute diverticulitis outcome prediction emergency complications CT volumetry segmentation living right liver donors automated segmentation U-NET colonoscopy colonoscopy preparation quality neuroendocrine tumors neuroendocrine neoplasms carcinoid gastroenteropancreatic GEP-NETs Pan-NENs SI-NETS colorectal cancer convolutional neural network (CNN) polyp detection polyp localization narrow-band image colon polyp Retinex gamma and sigmoid conversion YOLO colon capsule endoscopy convolutional neural network colorectal neoplasia bowel cleansing deep transfer learning multi-scale encoding weighted feature maps fusion image augmentation polyp inception module single-shot multibox detector (SSD) wireless capsule endoscopy images (WCE) pancreatic cystic lesions mucinous cystic neoplasm intraductal papillary mucinous neoplasm endoscopic ultrasound gut microbiome classification inflammatory bowel disease stacked generalization ensemble learning gastrointestinal disease early diagnosis medical image analysis polyp segmentation attention mechanism semantic segmentation healthcare informatics multiscale DenseNet lean fatty liver machine learning model fatty liver index OpenAI’s ChatGPT chatbot natural language processing (NLP) medical information gastroenterology patients’ questions breathomics volatile organic compounds automated diagnosis validation manifold learning ONCOSCREEN gastroscopy Gastro-BaseNet ImageNet endoscopy polypoid lesion identification polypoid lesion segmentation YOLO-V8 WCE images gastrointestinal disorders thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues Gastrointestinal disease (GID), the disease of the gastrointestinal tract, is one of the main contributors to disease burden around the world. GID causes 8 million deaths around the world per year and cost 120 billion dollars in the United States in 2018 alone. Simultaneously, the notion of artificial intelligence (AI) has gained great attention on a global level. Machine learning, a branch of AI extracting knowledge from large amounts of data, includes several common approaches, and a popular machine learning approach is the use of an artificial neural network (ANN), a group of neurons (information units) that are networked based on weights. An ANN normally has one input layer, one, two or three intermediate layers, and one output layer. A deep neural network (or deep learning) is an artificial neural network with a large number of intermediate layers, e.g., 5, 10 or even 1000. This Special Issue demonstrates the effectiveness and popularity of deep learning as a cutting-edge approach to the diagnosis and management of GID. This Special Issue covers a wide range of important topics including the classification, detection and segmentation of acute diverticulitis, colorectal cancer, gastric cancer, fatty liver, fecal material, inflammatory bowel disease, living-donor liver transplantation, neuroendocrine tumor and pancreatic cystic lesions. The Special Issue addresses the utility of explainable AI and large language models as well. In conclusion, this reprint will serve as an indispensable collection of original studies on the AI-based diagnosis and management of GID. 2024-05-14T14:35:48Z 2024-05-14T14:35:48Z 2024 book ONIX_20240514_9783725806539_420 9783725806539 9783725806546 https://directory.doabooks.org/handle/20.500.12854/137824 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9061 https://mdpi.com/books/pdfview/book/9061 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-0654-6 10.3390/books978-3-7258-0654-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725806539 9783725806546 322 open access |
| spellingShingle | deep learning transfer learning poorly differentiated adenocarcinoma colon machine learning artificial intelligence acute diverticulitis outcome prediction emergency complications CT volumetry segmentation living right liver donors automated segmentation U-NET colonoscopy colonoscopy preparation quality neuroendocrine tumors neuroendocrine neoplasms carcinoid gastroenteropancreatic GEP-NETs Pan-NENs SI-NETS colorectal cancer convolutional neural network (CNN) polyp detection polyp localization narrow-band image colon polyp Retinex gamma and sigmoid conversion YOLO colon capsule endoscopy convolutional neural network colorectal neoplasia bowel cleansing deep transfer learning multi-scale encoding weighted feature maps fusion image augmentation polyp inception module single-shot multibox detector (SSD) wireless capsule endoscopy images (WCE) pancreatic cystic lesions mucinous cystic neoplasm intraductal papillary mucinous neoplasm endoscopic ultrasound gut microbiome classification inflammatory bowel disease stacked generalization ensemble learning gastrointestinal disease early diagnosis medical image analysis polyp segmentation attention mechanism semantic segmentation healthcare informatics multiscale DenseNet lean fatty liver machine learning model fatty liver index OpenAI’s ChatGPT chatbot natural language processing (NLP) medical information gastroenterology patients’ questions breathomics volatile organic compounds automated diagnosis validation manifold learning ONCOSCREEN gastroscopy Gastro-BaseNet ImageNet endoscopy polypoid lesion identification polypoid lesion segmentation YOLO-V8 WCE images gastrointestinal disorders thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues Artificial Intelligence in Gastrointestinal Disease: Diagnosis and Management |
| title | Artificial Intelligence in Gastrointestinal Disease: Diagnosis and Management |
| title_full | Artificial Intelligence in Gastrointestinal Disease: Diagnosis and Management |
| title_fullStr | Artificial Intelligence in Gastrointestinal Disease: Diagnosis and Management |
| title_full_unstemmed | Artificial Intelligence in Gastrointestinal Disease: Diagnosis and Management |
| title_short | Artificial Intelligence in Gastrointestinal Disease: Diagnosis and Management |
| title_sort | artificial intelligence in gastrointestinal disease diagnosis and management |
| topic | deep learning transfer learning poorly differentiated adenocarcinoma colon machine learning artificial intelligence acute diverticulitis outcome prediction emergency complications CT volumetry segmentation living right liver donors automated segmentation U-NET colonoscopy colonoscopy preparation quality neuroendocrine tumors neuroendocrine neoplasms carcinoid gastroenteropancreatic GEP-NETs Pan-NENs SI-NETS colorectal cancer convolutional neural network (CNN) polyp detection polyp localization narrow-band image colon polyp Retinex gamma and sigmoid conversion YOLO colon capsule endoscopy convolutional neural network colorectal neoplasia bowel cleansing deep transfer learning multi-scale encoding weighted feature maps fusion image augmentation polyp inception module single-shot multibox detector (SSD) wireless capsule endoscopy images (WCE) pancreatic cystic lesions mucinous cystic neoplasm intraductal papillary mucinous neoplasm endoscopic ultrasound gut microbiome classification inflammatory bowel disease stacked generalization ensemble learning gastrointestinal disease early diagnosis medical image analysis polyp segmentation attention mechanism semantic segmentation healthcare informatics multiscale DenseNet lean fatty liver machine learning model fatty liver index OpenAI’s ChatGPT chatbot natural language processing (NLP) medical information gastroenterology patients’ questions breathomics volatile organic compounds automated diagnosis validation manifold learning ONCOSCREEN gastroscopy Gastro-BaseNet ImageNet endoscopy polypoid lesion identification polypoid lesion segmentation YOLO-V8 WCE images gastrointestinal disorders thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues |
| topic_facet | deep learning transfer learning poorly differentiated adenocarcinoma colon machine learning artificial intelligence acute diverticulitis outcome prediction emergency complications CT volumetry segmentation living right liver donors automated segmentation U-NET colonoscopy colonoscopy preparation quality neuroendocrine tumors neuroendocrine neoplasms carcinoid gastroenteropancreatic GEP-NETs Pan-NENs SI-NETS colorectal cancer convolutional neural network (CNN) polyp detection polyp localization narrow-band image colon polyp Retinex gamma and sigmoid conversion YOLO colon capsule endoscopy convolutional neural network colorectal neoplasia bowel cleansing deep transfer learning multi-scale encoding weighted feature maps fusion image augmentation polyp inception module single-shot multibox detector (SSD) wireless capsule endoscopy images (WCE) pancreatic cystic lesions mucinous cystic neoplasm intraductal papillary mucinous neoplasm endoscopic ultrasound gut microbiome classification inflammatory bowel disease stacked generalization ensemble learning gastrointestinal disease early diagnosis medical image analysis polyp segmentation attention mechanism semantic segmentation healthcare informatics multiscale DenseNet lean fatty liver machine learning model fatty liver index OpenAI’s ChatGPT chatbot natural language processing (NLP) medical information gastroenterology patients’ questions breathomics volatile organic compounds automated diagnosis validation manifold learning ONCOSCREEN gastroscopy Gastro-BaseNet ImageNet endoscopy polypoid lesion identification polypoid lesion segmentation YOLO-V8 WCE images gastrointestinal disorders thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues |
| url | ONIX_20240514_9783725806539_420 |