Detalhe da pesquisa
1.
Artificial intelligence for the detection of esophageal and esophagogastric junctional adenocarcinoma.
J Gastroenterol Hepatol
; 36(1): 131-136, 2021 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-32511793
2.
Endoscopic detection and differentiation of esophageal lesions using a deep neural network.
Gastrointest Endosc
; 91(2): 301-309.e1, 2020 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-31585124
3.
Automatic detection and classification of protruding lesions in wireless capsule endoscopy images based on a deep convolutional neural network.
Gastrointest Endosc
; 92(1): 144-151.e1, 2020 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-32084410
4.
Convolutional Neural Network for Differentiating Gastric Cancer from Gastritis Using Magnified Endoscopy with Narrow Band Imaging.
Dig Dis Sci
; 65(5): 1355-1363, 2020 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-31584138
5.
Artificial intelligence using a convolutional neural network for automatic detection of small-bowel angioectasia in capsule endoscopy images.
Dig Endosc
; 32(3): 382-390, 2020 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-31392767
6.
Clinical usefulness of a deep learning-based system as the first screening on small-bowel capsule endoscopy reading.
Dig Endosc
; 32(4): 585-591, 2020 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-31441972
7.
Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.
Esophagus
; 17(3): 250-256, 2020 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-31980977
8.
Novel computer-assisted diagnosis system for endoscopic disease activity in patients with ulcerative colitis.
Gastrointest Endosc
; 89(2): 416-421.e1, 2019 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-30367878
9.
Classification for invasion depth of esophageal squamous cell carcinoma using a deep neural network compared with experienced endoscopists.
Gastrointest Endosc
; 90(3): 407-414, 2019 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-31077698
10.
Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks.
Gastrointest Endosc
; 89(1): 25-32, 2019 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-30120958
11.
Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network.
Gastrointest Endosc
; 89(2): 357-363.e2, 2019 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-30670179
12.
Application of convolutional neural networks for evaluating Helicobacter pylori infection status on the basis of endoscopic images.
Scand J Gastroenterol
; 54(2): 158-163, 2019 Feb.
Artigo
em Inglês
| MEDLINE | ID: mdl-30879352
13.
Diagnosis using deep-learning artificial intelligence based on the endocytoscopic observation of the esophagus.
Esophagus
; 16(2): 180-187, 2019 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-30547352
14.
Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.
Gastric Cancer
; 21(4): 653-660, 2018 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-29335825
15.
Application of Convolutional Neural Networks for Detection of Superficial Nonampullary Duodenal Epithelial Tumors in Esophagogastroduodenoscopic Images.
Clin Transl Gastroenterol
; 11(3): e00154, 2020 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-32352719
16.
Stratification of gastric cancer risk using a deep neural network.
JGH Open
; 4(3): 466-471, 2020 Jun.
Artigo
em Inglês
| MEDLINE | ID: mdl-32514455
17.
Application of Convolutional Neural Networks in the Diagnosis of Helicobacter pylori Infection Based on Endoscopic Images.
EBioMedicine
; 25: 106-111, 2017 Nov.
Artigo
em Inglês
| MEDLINE | ID: mdl-29056541