An artificial intelligence algorithm is highly accurate for detecting endoscopic features of eosinophilic esophagitis

• Published in: Scientific reports Vol. 12; no. 1; p. 11115
• Main Authors: Römmele, Christoph, Mendel, Robert, Barrett, Caroline, Kiesl, Hans, Rauber, David, Rückert, Tobias, Kraus, Lisa, Heinkele, Jakob, Dhillon, Christine, Grosser, Bianca, Prinz, Friederike, Wanzl, Julia, Fleischmann, Carola, Nagl, Sandra, Schnoy, Elisabeth, Schlottmann, Jakob, Dellon, Evan S., Messmann, Helmut, Palm, Christoph, Ebigbo, Alanna
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.07.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705; 692/4020; 692/699; Algorithms; Artificial intelligence; Autoimmune diseases; Endoscopy; Esophageal diseases; Esophagitis; Esophagus; Gastrointestinal diseases; Humanities and Social Sciences; Leukocytes (eosinophilic); multidisciplinary; Science; Science (multidisciplinary)

The endoscopic features associated with eosinophilic esophagitis (EoE) may be missed during routine endoscopy. We aimed to develop and evaluate an Artificial Intelligence (AI) algorithm for detecting and quantifying the endoscopic features of EoE in white light images, supplemented by the EoE Endosc...