K. Waki, R. Ishihara, A. Shoji, Takahiro Inoue, Katunori Matsueda, M. Miyake, H. Fukuda, S. Shichijo, A. Maekawa, T. Kanesaka, Y. Takeuchi, K. Higashino, N. Uedo, T. Michida, Yasuhito Tanaka, Yusuke Kato, T. Tada
{"title":"Artificial Intelligence–Based Diagnostic System for Esophageal Endoscopy","authors":"K. Waki, R. Ishihara, A. Shoji, Takahiro Inoue, Katunori Matsueda, M. Miyake, H. Fukuda, S. Shichijo, A. Maekawa, T. Kanesaka, Y. Takeuchi, K. Higashino, N. Uedo, T. Michida, Yasuhito Tanaka, Yusuke Kato, T. Tada","doi":"10.2530/jslsm.jslsm-42_0022","DOIUrl":null,"url":null,"abstract":"In cooperation with AI Medical Service Inc., we have developed various artificial intelligence (AI)-based diagnostic systems for endoscopy of various organs. Particularly for esophageal squamous cell carcinoma, we have developed AI-based systems that support all phases of clinical diagnostic processes. We recently reported that AI assistance significantly improved the detection rate of lesions without reducing specificity on videos simulating overlooking situation. We are currently moving toward commercialization of the AI-based endoscopic diagnostic system for esophageal cancer.","PeriodicalId":19350,"journal":{"name":"Nippon Laser Igakkaishi","volume":"2 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_0022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In cooperation with AI Medical Service Inc., we have developed various artificial intelligence (AI)-based diagnostic systems for endoscopy of various organs. Particularly for esophageal squamous cell carcinoma, we have developed AI-based systems that support all phases of clinical diagnostic processes. We recently reported that AI assistance significantly improved the detection rate of lesions without reducing specificity on videos simulating overlooking situation. We are currently moving toward commercialization of the AI-based endoscopic diagnostic system for esophageal cancer.
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