Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy

Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy

Abstract Artificial intelligence (AI) is widely used to analyze gastrointestinal (GI) endoscopy image data. AI has led to several clinically approved algorithms for polyp detection, but application of AI beyond this specific task is limited by the high cost of manual annotations. Here, we show that...

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Bibliographic Details
Main Authors: Lukas Buendgens, Didem Cifci, Narmin Ghaffari Laleh, Marko van Treeck, Maria T. Koenen, Henning W. Zimmermann, Till Herbold, Thomas Joachim Lux, Alexander Hann, Christian Trautwein, Jakob Nikolas Kather
Format: Article
Language:English
Published: Nature Portfolio 2022-03-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-08773-1

Internet

https://doi.org/10.1038/s41598-022-08773-1

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