日本総合健診医学会 第51回大会・共催シンポジウム1 検診に役立つ内視鏡診療─画像強調観察からAIまで 対策型冑癌検診における人工知能、AIの可能性
Author:
Affiliation:
1. Gastroenterological Endoscopy, Tokyo Medical University
2. Department of Gastroenterology, Nagasaki Harbor Medical Center
Publisher
Japan Society of Health Evaluation and Promotion
Subject
Ocean Engineering
Link
https://www.jstage.jst.go.jp/article/jhep/50/6/50_560/_pdf
Reference9 articles.
1. 1) Yip HC, Uedo N, Chan SM, et al: An international survey on recognition and characterization of atrophic gastritis and intestinal metaplasia. Endosc Int Open. 2020; 08(10) : E1365-70.
2. 2) Hirasawa T, Aoyama K, Tanimoto T, et al: Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images. Gastric Cancer 2018; 21: 653-60. doi: 10.1007/s10120-018-0793-2
3. 3) Ikenoyama Y, Hirasawa T, Ishioka M, et al: Detecting early gastric cancer: Comparison between the diagnostic ability of convolutional neural networks and endoscopists. Dig Endosc 2021; 33: 141-50. doi: 10.1111/den.13688
4. 4) Horiuchi Y, Hirasawa T, Ishizuka N, et al: Performance of a computer-aided diagnosis system in diagnosing early gastric cancer using magnifying endoscopy videos with narrow-band imaging (with videos). Gastrointest Endosc 2020; 92: 856-65. doi: 10.1016/j.gie.2020.04.079
5. 5) Ueyama H, Kato Y, Akazawa Y, et al: Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging. J Gastroenterol Hepatol 2021; 36: 482-9. doi: 10.1111/jgh.15190
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