Assessment of an electronic learning system for colon capsule endoscopy: a pilot study

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


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

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

2011 ◽  
Vol 43 (4) ◽  
pp. 300-304 ◽  
Author(s):  
Cristiano Spada ◽  
Cesare Hassan ◽  
Marcello Ingrosso ◽  
Alessandro Repici ◽  
Maria Elena Riccioni ◽  
...  

2011 ◽  
Vol 43 ◽  
pp. S261
Author(s):  
C. Spada ◽  
C. Hassan ◽  
M. Ingrosso ◽  
A. Simone ◽  
M.E. Riccioni ◽  
...  

2011 ◽  
Vol 73 (4) ◽  
pp. AB305-AB306
Author(s):  
Laura Ramos ◽  
Onofre Alarcón-Fernández ◽  
Antonio Z. Gimeno-García ◽  
David Nicolás-Pérez ◽  
Zaida Adrián-De-Ganzo ◽  
...  

2011 ◽  
Vol 140 (5) ◽  
pp. S-119 ◽  
Author(s):  
Dobromir Filip ◽  
Orly Yadid-Pecht ◽  
Christopher N. Andrews ◽  
Martin P. Mintchev

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