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Development of a deep learning-based software for calculating cleansing score in small bowel capsule endoscopy.


ABSTRACT: A standardized small bowel (SB) cleansing scale is currently not available. The aim of this study was to develop an automated calculation software for SB cleansing score using deep learning. Consecutively performed capsule endoscopy cases were enrolled from three hospitals. A 5-step scoring system based on mucosal visibility was trained for deep learning in the training set. Performance of the trained software was evaluated in the validation set. Average cleansing score (1.0 to 5.0) by deep learning was compared to clinical grading (A to C) reviewed by clinicians. Cleansing scores decreased as clinical grading worsened (scores of 4.1, 3.5, and 2.9 for grades A, B, and C, respectively, P?

SUBMITTER: Nam JH 

PROVIDER: S-EPMC7904767 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Development of a deep learning-based software for calculating cleansing score in small bowel capsule endoscopy.

Nam Ji Hyung JH   Hwang Youngbae Y   Oh Dong Jun DJ   Park Junseok J   Kim Ki Bae KB   Jung Min Kyu MK   Lim Yun Jeong YJ  

Scientific reports 20210224 1


A standardized small bowel (SB) cleansing scale is currently not available. The aim of this study was to develop an automated calculation software for SB cleansing score using deep learning. Consecutively performed capsule endoscopy cases were enrolled from three hospitals. A 5-step scoring system based on mucosal visibility was trained for deep learning in the training set. Performance of the trained software was evaluated in the validation set. Average cleansing score (1.0 to 5.0) by deep lear  ...[more]

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