582 related articles for article (PubMed ID: 30120958)
21. Esophageal squamous dysplasia and cancer: Is artificial intelligence our best weapon?
Hussein M; Everson M; Haidry R
Best Pract Res Clin Gastroenterol; 2021; 52-53():101723. PubMed ID: 34172257
[TBL] [Abstract][Full Text] [Related]
22. Diagnosis of gastric lesions through a deep convolutional neural network.
Zhang L; Zhang Y; Wang L; Wang J; Liu Y
Dig Endosc; 2021 Jul; 33(5):788-796. PubMed ID: 32961597
[TBL] [Abstract][Full Text] [Related]
23. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm.
Lee JH; Kim DH; Jeong SN; Choi SH
J Dent; 2018 Oct; 77():106-111. PubMed ID: 30056118
[TBL] [Abstract][Full Text] [Related]
24. Endoscopic Images by a Single-Shot Multibox Detector for the Identification of Early Cancerous Lesions in the Esophagus: A Pilot Study.
Wang YK; Syu HY; Chen YH; Chung CS; Tseng YS; Ho SY; Huang CW; Wu IC; Wang HC
Cancers (Basel); 2021 Jan; 13(2):. PubMed ID: 33477274
[TBL] [Abstract][Full Text] [Related]
25. Computer-Aided Diagnosis Based on Convolutional Neural Network System for Colorectal Polyp Classification: Preliminary Experience.
Komeda Y; Handa H; Watanabe T; Nomura T; Kitahashi M; Sakurai T; Okamoto A; Minami T; Kono M; Arizumi T; Takenaka M; Hagiwara S; Matsui S; Nishida N; Kashida H; Kudo M
Oncology; 2017; 93 Suppl 1():30-34. PubMed ID: 29258081
[TBL] [Abstract][Full Text] [Related]
26. Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network.
Han SS; Park GH; Lim W; Kim MS; Na JI; Park I; Chang SE
PLoS One; 2018; 13(1):e0191493. PubMed ID: 29352285
[TBL] [Abstract][Full Text] [Related]
27. Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network.
Aoki T; Yamada A; Aoyama K; Saito H; Tsuboi A; Nakada A; Niikura R; Fujishiro M; Oka S; Ishihara S; Matsuda T; Tanaka S; Koike K; Tada T
Gastrointest Endosc; 2019 Feb; 89(2):357-363.e2. PubMed ID: 30670179
[TBL] [Abstract][Full Text] [Related]
28. Use of a convolutional neural network for classifying microvessels of superficial esophageal squamous cell carcinomas.
Uema R; Hayashi Y; Tashiro T; Saiki H; Kato M; Amano T; Tani M; Yoshihara T; Inoue T; Kimura K; Iwatani S; Sakatani A; Yoshii S; Tsujii Y; Shinzaki S; Iijima H; Takehara T
J Gastroenterol Hepatol; 2021 Aug; 36(8):2239-2246. PubMed ID: 33694189
[TBL] [Abstract][Full Text] [Related]
29. Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images.
Miwa T; Minoda R; Yamaguchi T; Kita SI; Osaka K; Takeda H; Kanemaru SI; Omori K
Auris Nasus Larynx; 2022 Feb; 49(1):11-17. PubMed ID: 33824034
[TBL] [Abstract][Full Text] [Related]
30. [Application of deep convolutional neural networks in the diagnosis of laryngeal squamous cell carcinoma based on narrow band imaging endoscopy].
Hu R; Zhong Q; Xu ZG; Huang LY; Cheng Y; Wang YR; He YD; Cheng Y
Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi; 2021 May; 56(5):454-458. PubMed ID: 34010998
[No Abstract] [Full Text] [Related]
31. Efficacy of Digestive Endoscope Based on Artificial Intelligence System in Diagnosing Early Esophageal Carcinoma.
Zhao Z; Li M; Liu P; Yu J; Zhao H
Comput Math Methods Med; 2022; 2022():9018939. PubMed ID: 35761840
[TBL] [Abstract][Full Text] [Related]
32. A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR.
Yang H; Li X; Zhang S; Li Y; Zhu Z; Shen J; Dai N; Zhou F
Spectrochim Acta A Mol Biomol Spectrosc; 2023 Mar; 289():122210. PubMed ID: 36508904
[TBL] [Abstract][Full Text] [Related]
33. Artificial intelligence using a convolutional neural network for automatic detection of small-bowel angioectasia in capsule endoscopy images.
Tsuboi A; Oka S; Aoyama K; Saito H; Aoki T; Yamada A; Matsuda T; Fujishiro M; Ishihara S; Nakahori M; Koike K; Tanaka S; Tada T
Dig Endosc; 2020 Mar; 32(3):382-390. PubMed ID: 31392767
[TBL] [Abstract][Full Text] [Related]
34. Artificial intelligence detection of distal radius fractures: a comparison between the convolutional neural network and professional assessments.
Gan K; Xu D; Lin Y; Shen Y; Zhang T; Hu K; Zhou K; Bi M; Pan L; Wu W; Liu Y
Acta Orthop; 2019 Aug; 90(4):394-400. PubMed ID: 30942136
[TBL] [Abstract][Full Text] [Related]
35. Artificial intelligence for detecting superficial esophageal squamous cell carcinoma under multiple endoscopic imaging modalities: A multicenter study.
Yuan XL; Guo LJ; Liu W; Zeng XH; Mou Y; Bai S; Pan ZG; Zhang T; Pu WF; Wen C; Wang J; Zhou ZD; Feng J; Hu B
J Gastroenterol Hepatol; 2022 Jan; 37(1):169-178. PubMed ID: 34532890
[TBL] [Abstract][Full Text] [Related]
36. Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network.
Wang L; Yang S; Yang S; Zhao C; Tian G; Gao Y; Chen Y; Lu Y
World J Surg Oncol; 2019 Jan; 17(1):12. PubMed ID: 30621704
[TBL] [Abstract][Full Text] [Related]
37. Real-time artificial intelligence for endoscopic diagnosis of early esophageal squamous cell cancer (with video).
Yang XX; Li Z; Shao XJ; Ji R; Qu JY; Zheng MQ; Sun YN; Zhou RC; You H; Li LX; Feng J; Yang XY; Li YQ; Zuo XL
Dig Endosc; 2021 Nov; 33(7):1075-1084. PubMed ID: 33275789
[TBL] [Abstract][Full Text] [Related]
38. Evaluation of double vital staining with lugol's iodine and methylene blue in diagnosing superficial esophageal lesions.
Peng G; Long Q; Wu Y; Zhao J; Chen L; Li X
Scand J Gastroenterol; 2011 Apr; 46(4):406-13. PubMed ID: 21189106
[TBL] [Abstract][Full Text] [Related]
39. Narrow-band imaging endoscopy with magnification is useful for detecting metachronous superficial pharyngeal cancer in patients with esophageal squamous cell carcinoma.
Nonaka S; Saito Y; Oda I; Kozu T; Saito D
J Gastroenterol Hepatol; 2010 Feb; 25(2):264-9. PubMed ID: 19874445
[TBL] [Abstract][Full Text] [Related]
40. Deep Convolutional Neural Networks for breast cancer screening.
Chougrad H; Zouaki H; Alheyane O
Comput Methods Programs Biomed; 2018 Apr; 157():19-30. PubMed ID: 29477427
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]