1114 ARTIFICIAL INTELLIGENCE, TRAINED WITH A ROUGH BINARY CLASSIFICATION, CAN SELECT SIGNIFICANT IMAGES OF CAPSULE ENDOSCOPY. - 09/06/20
Doi : 10.1016/j.gie.2020.03.875
Junseok Park 1, Youngbae Hwang 2, Yun Jeong Lim 3, Ji Hyung Nam 3, Dong Jun Oh 3, Hyun Joo Song 4, Ki Bae Kim 5, Su Hwan Kim 6, Min Kyu Jung 7
1 Digestive Disease Center, Institute for Digestive Research, Department of Internal Medicine, Soonchunhyang University College of Medicine, Seoul, Yongsan gu, Korea (the Republic of)
2 Department of Electronics Engineering, Chungbuk National University, Cheongju, Chungchungbuk do, Korea (the Republic of)
3 Division of Gastroenterology, Department of Internal Medicine, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Gyeonggi do, Korea (the Republic of)
4 Department of Internal Medicine, Jeju National University School of Medicine, Jeju, Jeju, Korea (the Republic of)
5 Department of Internal Medicine, Chungbuk National University College of Medicine, Cheongju, Chungchungbuk do, Korea (the Republic of)
6 Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Dongjak gu, Korea (the Republic of)
7 Division of Gastroenterology and Hepatology, Department of Internal Medicine, Kyungpook National University Hospital, Daegu, Kyungsangbuk do, Korea (the Republic of)
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© 2020
Pubblicato da Elsevier Masson SAS.
Vol 91 - N° 6S
P. AB98 - giugno 2020 Ritorno al numero
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