T. Hirasawa, Y. Ikenoyama, Mitsuaki Ishioka, K. Namikawa, Y. Horiuchi, Hirotaka Nakashima, T. Tada, J. Fujisaki
{"title":"应用人工智能(AI)进行胃癌内镜诊断","authors":"T. Hirasawa, Y. Ikenoyama, Mitsuaki Ishioka, K. Namikawa, Y. Horiuchi, Hirotaka Nakashima, T. Tada, J. Fujisaki","doi":"10.2530/JSLSM.JSLSM-42_0013","DOIUrl":null,"url":null,"abstract":"Image recognition using artificial intelligence (AI) has made great strides due to innovations in machine learning, deep learning, and high-performance graphics processing units. Currently, it is considered that AI has exceeded human capabilities in image recognition. In the field of gastric cancer, research on AI-based diagnoses, such as anatomical classification of esophagogastroduodenoscopy images, identification of Helicobacter pylori infection, and detection and qualitative diagnosis of gastric cancer, is being performed, and accuracy equivalent to that of endoscopists has been reported. However, there are some drawbacks with the use of medical AI that make it less acceptable than existing medical devices, and there are significant hurdles before it can be introduced into clinical practice. In the near future, AI is expected to be introduced to the field of gastric cancer diagnosis and improve the quality of medical care.","PeriodicalId":19350,"journal":{"name":"Nippon Laser Igakkaishi","volume":"41 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Endoscopic Diagnosis of Gastric Cancer Utilizing Artificial Intelligence (AI)\",\"authors\":\"T. Hirasawa, Y. Ikenoyama, Mitsuaki Ishioka, K. Namikawa, Y. Horiuchi, Hirotaka Nakashima, T. Tada, J. Fujisaki\",\"doi\":\"10.2530/JSLSM.JSLSM-42_0013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image recognition using artificial intelligence (AI) has made great strides due to innovations in machine learning, deep learning, and high-performance graphics processing units. Currently, it is considered that AI has exceeded human capabilities in image recognition. In the field of gastric cancer, research on AI-based diagnoses, such as anatomical classification of esophagogastroduodenoscopy images, identification of Helicobacter pylori infection, and detection and qualitative diagnosis of gastric cancer, is being performed, and accuracy equivalent to that of endoscopists has been reported. However, there are some drawbacks with the use of medical AI that make it less acceptable than existing medical devices, and there are significant hurdles before it can be introduced into clinical practice. In the near future, AI is expected to be introduced to the field of gastric cancer diagnosis and improve the quality of medical care.\",\"PeriodicalId\":19350,\"journal\":{\"name\":\"Nippon Laser Igakkaishi\",\"volume\":\"41 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nippon Laser Igakkaishi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2530/JSLSM.JSLSM-42_0013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nippon Laser Igakkaishi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2530/JSLSM.JSLSM-42_0013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Endoscopic Diagnosis of Gastric Cancer Utilizing Artificial Intelligence (AI)
Image recognition using artificial intelligence (AI) has made great strides due to innovations in machine learning, deep learning, and high-performance graphics processing units. Currently, it is considered that AI has exceeded human capabilities in image recognition. In the field of gastric cancer, research on AI-based diagnoses, such as anatomical classification of esophagogastroduodenoscopy images, identification of Helicobacter pylori infection, and detection and qualitative diagnosis of gastric cancer, is being performed, and accuracy equivalent to that of endoscopists has been reported. However, there are some drawbacks with the use of medical AI that make it less acceptable than existing medical devices, and there are significant hurdles before it can be introduced into clinical practice. In the near future, AI is expected to be introduced to the field of gastric cancer diagnosis and improve the quality of medical care.