Kim, Ji Hyun; Nam, Seung-Joo; Park, Sung Chul
World journal of gastroenterology
2021Jun ; 27 ( 24 ) :3543-3555.
PMID : 34239268
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Kim, Ji Hyun - Division of Gastroenterology and Hepatology, Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon 24289, Kangwon Do, South Korea.
Nam, Seung-Joo - Division of Gastroenterology and Hepatology, Department of Internal Medicine,
Park, Sung Chul - Division of Gastroenterology and Hepatology, Department of Internal Medicine,
ABSTRACT
Recently, studies in many medical fields have reported that image analysis based on artificial intelligence (AI) can be used to analyze structures or features that are difficult to identify with human eyes. To diagnose early gastric cancer, related efforts such as narrow-band imaging technology are on-going. However, diagnosis is often difficult. Therefore, a diagnostic method based on AI for endoscopic imaging was developed and its effectiveness was confirmed in many studies. The gastric cancer diagnostic program based on AI showed relatively high diagnostic accuracy and could differentially diagnose non-neoplastic lesions including benign gastric ulcers and dysplasia. An AI system has also been developed that helps to predict the invasion depth of gastric cancer through endoscopic images and observe the stomach during endoscopy without blind spots. Therefore, if AI is used in the field of endoscopy, it is expected to aid in the diagnosis of gastric neoplasms and determine the application of endoscopic therapy by predicting the invasion depth. CI - ?’The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
keyword
Artificial intelligence; Convolutional neural network; Diagnosis; Esophagogastroduodenoscopy; Gastric neoplasm; Invasion depth
MESH
Artificial Intelligence, Endoscopy, Humans, Image Processing, Computer-Assisted, Narrow Band Imaging, *Stomach Neoplasms/diagnostic imaging
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