Artificial intelligence in gastroenterology: A state-of-the-art review
| Autor: | Paul T. Kroner, Obaie Mzaik, Jeanin E. van Hooft, Megan M. L. Engels, Benjamin S. Glicksberg, Hashem B. El-Serag, Michael B. Wallace, Chayakrit Krittanawong, Kipp W. Johnson |
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| Rok vydání: | 2021 |
| Předmět: |
Diagnostic Imaging
Artificial intelligence medicine.medical_specialty Review Clinical applications Inflammatory bowel disease Gastroenterology law.invention Lesion Barrett Esophagus Capsule endoscopy law Internal medicine Machine learning medicine Humans Esophagus business.industry Endoscopy Deep learning General Medicine Hepatology medicine.disease digestive system diseases medicine.anatomical_structure Dysplasia Hepatocellular carcinoma medicine.symptom business Pancreas |
| Zdroj: | World Journal of Gastroenterology World Journal of Gastroenterology, 27(40), 6794-6824. BAISHIDENG PUBLISHING GROUP INC World Journal of Gastroenterology, 27(40), 6794-6824. Baishideng Publishing Group Inc. |
| ISSN: | 1007-9327 |
| DOI: | 10.3748/wjg.v27.i40.6794 |
| Popis: | The development of artificial intelligence (AI) has increased dramatically in the last 20 years, with clinical applications progressively being explored for most of the medical specialties. The field of gastroenterology and hepatology, substantially reliant on vast amounts of imaging studies, is not an exception. The clinical applications of AI systems in this field include the identification of premalignant or malignant lesions (e.g., identification of dysplasia or esophageal adenocarcinoma in Barrett’s esophagus, pancreatic malignancies), detection of lesions (e.g., polyp identification and classification, small-bowel bleeding lesion on capsule endoscopy, pancreatic cystic lesions), development of objective scoring systems for risk stratification, predicting disease prognosis or treatment response [e.g., determining survival in patients post-resection of hepatocellular carcinoma), determining which patients with inflammatory bowel disease (IBD) will benefit from biologic therapy], or evaluation of metrics such as bowel preparation score or quality of endoscopic examination. The objective of this comprehensive review is to analyze the available AI-related studies pertaining to the entirety of the gastrointestinal tract, including the upper, middle and lower tracts; IBD; the hepatobiliary system; and the pancreas, discussing the findings and clinical applications, as well as outlining the current limitations and future directions in this field. |
| Databáze: | OpenAIRE |
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