Thomas Lux on "Assisted documentation as a new focus for artificial intelligence in endoscopy:...

Thomas Lux on "Assisted documentation as a new focus for artificial intelligence in endoscopy: the precedent of reliable withdrawal time and image reporting"
A deep learning algorithm distinguishing different endoscopic image content was trained to produce a predicted withdrawal time and extract relevant images. Comparison with video-based measurement of withdrawal time showed a median absolute difference of 0.4 minutes for AI prediction vs. 2.0 minutes for the standard reported withdrawal time. AI-generated documentation captured the cecum in 98/100 examinations vs. 88/100 for examiners’ original photodocumentation. Real-time capability was also demonstrated, suggesting its future potential for standardized reporting with reduced workload.
Find the article at: doi.org/10.1055/a-2122-1671
Thomas J. Lux, Zita Saßmannshausen, Ioannis Kafetzis et al. Assisted documentation as a new focus for artificial intelligence in endoscopy: the precedent of reliable withdrawal time and image reporting
Endoscopy 2023; 55: 1118-1123 DOI 10.1055/a-2122-1671 ISSN 0013-726X © 2023. The Author(s). The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License