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1.
The use of a real-time computer-aided detection system for visible lesions in the Barrett's esophagus during live endoscopic procedures, a pilot study.
Gastrointest Endosc
; 2024 Apr 09.
Artículo
en Inglés
| MEDLINE | ID: mdl-38604297
2.
COMPUTER-AIDED DIAGNOSIS IMPROVES CHARACTERIZATION OF BARRETT'S NEOPLASIA BY GENERAL ENDOSCOPISTS.
Gastrointest Endosc
; 2024 Apr 16.
Artículo
en Inglés
| MEDLINE | ID: mdl-38636819
3.
Deep-Learning System Detects Neoplasia in Patients With Barrett's Esophagus With Higher Accuracy Than Endoscopists in a Multistep Training and Validation Study With Benchmarking.
Gastroenterology
; 158(4): 915-929.e4, 2020 03.
Artículo
en Inglés
| MEDLINE | ID: mdl-31759929
4.
Blue-light imaging and linked-color imaging improve visualization of Barrett's neoplasia by nonexpert endoscopists.
Gastrointest Endosc
; 91(5): 1050-1057, 2020 05.
Artículo
en Inglés
| MEDLINE | ID: mdl-31904377
5.
Deep learning algorithm detection of Barrett's neoplasia with high accuracy during live endoscopic procedures: a pilot study (with video).
Gastrointest Endosc
; 91(6): 1242-1250, 2020 06.
Artículo
en Inglés
| MEDLINE | ID: mdl-31926965
6.
Towards a robust and compact deep learning system for primary detection of early Barrett's neoplasia: Initial image-based results of training on a multi-center retrospectively collected data set.
United European Gastroenterol J
; 11(4): 324-336, 2023 05.
Artículo
en Inglés
| MEDLINE | ID: mdl-37095718
7.
Toward improved endoscopic surveillance with multidiameter single fiber reflectance spectroscopy in patients with Barrett's esophagus.
J Biophotonics
; 14(4): e202000351, 2021 04.
Artículo
en Inglés
| MEDLINE | ID: mdl-33410602
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