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Deep learning in negative small-bowel capsule endoscopy improves small-bowel lesion detection and diagnostic yield.
Choi, Kyung Seok; Park, DoGyeom; Kim, Jin Su; Cheung, Dae Young; Lee, Bo-In; Cho, Young-Seok; Kim, Jin Il; Lee, Seungchul; Lee, Han Hee.
Affiliation
  • Choi KS; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
  • Park D; Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Korea.
  • Kim JS; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
  • Cheung DY; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
  • Lee BI; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
  • Cho YS; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
  • Kim JI; Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
  • Lee S; Institute for Convergence Research and Education in Advanced Technology, Yonsei University, Seoul, Korea.
  • Lee HH; Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Korea.
Dig Endosc ; 36(4): 437-445, 2024 Apr.
Article in En | MEDLINE | ID: mdl-37612137
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Capsule Endoscopy / Deep Learning Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Dig Endosc Journal subject: DIAGNOSTICO POR IMAGEM / GASTROENTEROLOGIA Year: 2024 Document type: Article Country of publication: Australia
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Capsule Endoscopy / Deep Learning Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Dig Endosc Journal subject: DIAGNOSTICO POR IMAGEM / GASTROENTEROLOGIA Year: 2024 Document type: Article Country of publication: Australia