scholarly journals Castor oil as booster for colon capsule endoscopy preparation reduction: A prospective pilot study and patient questionnaire

Author(s):  
Kota Takashima ◽  
Yoriaki Komeda ◽  
Toshiharu Sakurai ◽  
Sho Masaki ◽  
Tomoyuki Nagai ◽  
...  
2021 ◽  
Vol 12 (4) ◽  
pp. 79-89
Author(s):  
Kota Takashima ◽  
Yoriaki Komeda ◽  
Toshiharu Sakurai ◽  
Sho Masaki ◽  
Tomoyuki Nagai ◽  
...  

2018 ◽  
Vol 06 (08) ◽  
pp. E1044-E1050 ◽  
Author(s):  
Maria Magdalena Buijs ◽  
Mohammed Hossain Ramezani ◽  
Jürgen Herp ◽  
Rasmus Kroijer ◽  
Morten Kobaek-Larsen ◽  
...  

Abstract Background and study aims The aim of this study was to develop a machine learning-based model to classify bowel cleansing quality and to test this model in comparison to a pixel analysis model and assessments by four colon capsule endoscopy (CCE) readers. Methods A pixel analysis and a machine learning-based model with four cleanliness classes (unacceptable, poor, fair and good) were developed to classify CCE videos. Cleansing assessments by four CCE readers in 41 videos from a previous study were compared to the results both models yielded in this pilot study. Results The machine learning-based model classified 47 % of the videos in agreement with the averaged classification by CCE readers, as compared to 32 % by the pixel analysis model. A difference of more than one class was detected in 12 % of the videos by the machine learning-based model and in 32 % by the pixel analysis model, as the latter tended to overestimate cleansing quality. A specific analysis of unacceptable videos found that the pixel analysis model classified almost all of them as fair or good, whereas the machine learning-based model identified five out of 11 videos in agreement with at least one CCE reader as unacceptable. Conclusions The machine learning-based model was superior to the pixel analysis in classifying bowel cleansing quality, due to a higher sensitivity to unacceptable and poor cleansing quality. The machine learning-based model can be further improved by coming to a consensus on how to classify cleanliness of a complete CCE video, by means of an expert panel.


2018 ◽  
Vol 31 (2) ◽  
pp. 164-172 ◽  
Author(s):  
Naoki Ohmiya ◽  
Naoki Hotta ◽  
Shoji Mitsufuji ◽  
Masanao Nakamura ◽  
Takafumi Omori ◽  
...  

2014 ◽  
Vol 37 (3) ◽  
pp. 101-106 ◽  
Author(s):  
Laura Ramos ◽  
Onofre Alarcón ◽  
Zaida Adrian ◽  
Antonio Z. Gimeno-García ◽  
David Nicolás-Pérez ◽  
...  

2015 ◽  
Vol 51 (6) ◽  
pp. 579-585 ◽  
Author(s):  
Hirotsugu Watabe ◽  
Tetsuya Nakamura ◽  
Atsuo Yamada ◽  
Yasuo Kakugawa ◽  
Sadaharu Nouda ◽  
...  

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