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Convolutional neural network-based object detection model to identify gastrointestinal stromal tumors in endoscopic ultrasound images.
Oh, Chang Kyo; Kim, Taewan; Cho, Yu Kyung; Cheung, Dae Young; Lee, Bo-In; Cho, Young-Seok; Kim, Jin Il; Choi, Myung-Gyu; Lee, Han Hee; Lee, Seungchul.
Affiliation
  • Oh CK; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Kim T; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, South Korea.
  • Cho YK; Postech-Catholic Biomedical Engineering Institute, Pohang University of Science and Technology (POSTECH), Pohang, South Korea.
  • Cheung DY; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Lee BI; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Cho YS; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Kim JI; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Choi MG; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Lee HH; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Lee S; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
J Gastroenterol Hepatol ; 36(12): 3387-3394, 2021 Dec.
Article in En | MEDLINE | ID: mdl-34369001
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer / Gastrointestinal Stromal Tumors Type of study: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: J Gastroenterol Hepatol Journal subject: GASTROENTEROLOGIA Year: 2021 Type: Article Affiliation country: South Korea
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer / Gastrointestinal Stromal Tumors Type of study: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: J Gastroenterol Hepatol Journal subject: GASTROENTEROLOGIA Year: 2021 Type: Article Affiliation country: South Korea