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May 6, 2022United European Gastroenterology JournalOpen Access

A new artificial intelligence system successfully detects and localises early neoplasia in Barrett's esophagus by using convolutional neural networks

Mohamed Hussein Juana González‐Bueno Puyal David Lines Vinay Sehgal Dániel Tóth Omer F. Ahmad Rawen Kader Martin Everson Gideon Lipman Jacobo Ortiz Fernández‐Sordo Krish Ragunath José Miguel Esteban López-Jamar Raf Bisschops Matthew Banks Michael Haefner Peter Mountney Danail Stoyanov Laurence Lovat Rehan Haidry

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Abstract

Our CNNs classify and localise dysplastic Barrett's Esophagus potentially supporting endoscopists during surveillance.

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Cite This Study

Hussein et al. (2022) studied this question.

synapsesocial.com/papers/69d979fec7f0c3ae80a3d9eb https://doi.org/10.1002/ueg2.12233

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Synapse has enriched 5 related papers. Consider them for comparative context:

1Barrett Esophagus Length, Nodularity, and Low-grade Dysplasia are Predictive of Progression to Esophageal AdenocarcinomaCohort Study · 2018 · 39 citations
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4Machine Learning Creates a Simple Endoscopic Classification System that Improves Dysplasia Detection in Barrett’s Oesophagus amongst Non-expert EndoscopistsOriginal Research · 2018 · 27 citations
5Metabolic Dysfunction‐Associated Steatotic Disease and Genetic Risk in Germany—An Observational Real‐World Cohort StudyUnited European Gastroenterology Journal · Thu,

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