496 related articles for article (PubMed ID: 33328124)
1. Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation.
Liu KL; Wu T; Chen PT; Tsai YM; Roth H; Wu MS; Liao WC; Wang W
Lancet Digit Health; 2020 Jun; 2(6):e303-e313. PubMed ID: 33328124
[TBL] [Abstract][Full Text] [Related]
2. Pancreatic Cancer Detection on CT Scans with Deep Learning: A Nationwide Population-based Study.
Chen PT; Wu T; Wang P; Chang D; Liu KL; Wu MS; Roth HR; Lee PC; Liao WC; Wang W
Radiology; 2023 Jan; 306(1):172-182. PubMed ID: 36098642
[TBL] [Abstract][Full Text] [Related]
3. Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis.
Ma H; Liu ZX; Zhang JJ; Wu FT; Xu CF; Shen Z; Yu CH; Li YM
World J Gastroenterol; 2020 Sep; 26(34):5156-5168. PubMed ID: 32982116
[TBL] [Abstract][Full Text] [Related]
4. Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset.
Panda A; Korfiatis P; Suman G; Garg SK; Polley EC; Singh DP; Chari ST; Goenka AH
Med Phys; 2021 May; 48(5):2468-2481. PubMed ID: 33595105
[TBL] [Abstract][Full Text] [Related]
5. Radiomic Features at CT Can Distinguish Pancreatic Cancer from Noncancerous Pancreas.
Chen PT; Chang D; Yen H; Liu KL; Huang SY; Roth H; Wu MS; Liao WC; Wang W
Radiol Imaging Cancer; 2021 Jul; 3(4):e210010. PubMed ID: 34241550
[TBL] [Abstract][Full Text] [Related]
6. [Establishment and clinical testing of pancreatic cancer Faster R-CNN AI system based on fast regional convolutional neural network].
Yang SJ; Lu Y; Zheng XF; Zhang YJ; Xin FJ; Sun P; Li Y; Liu SS; Li S; Guo YT; Liu SL
Zhonghua Wai Ke Za Zhi; 2020 Jul; 58(7):520-524. PubMed ID: 32610422
[No Abstract] [Full Text] [Related]
7. Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.
Joo MW; Ko T; Kim MS; Lee YS; Shin SH; Chung YG; Lee HK
Clin Orthop Relat Res; 2023 Nov; 481(11):2247-2256. PubMed ID: 37615504
[TBL] [Abstract][Full Text] [Related]
8. Preoperative Prediction of Pancreatic Neuroendocrine Neoplasms Grading Based on Enhanced Computed Tomography Imaging: Validation of Deep Learning with a Convolutional Neural Network.
Luo Y; Chen X; Chen J; Song C; Shen J; Xiao H; Chen M; Li ZP; Huang B; Feng ST
Neuroendocrinology; 2020; 110(5):338-350. PubMed ID: 31525737
[TBL] [Abstract][Full Text] [Related]
9. Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.
Zhang C; Sun X; Dang K; Li K; Guo XW; Chang J; Yu ZQ; Huang FY; Wu YS; Liang Z; Liu ZY; Zhang XG; Gao XL; Huang SH; Qin J; Feng WN; Zhou T; Zhang YB; Fang WJ; Zhao MF; Yang XN; Zhou Q; Wu YL; Zhong WZ
Oncologist; 2019 Sep; 24(9):1159-1165. PubMed ID: 30996009
[TBL] [Abstract][Full Text] [Related]
10. Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.
Xu M; Qi S; Yue Y; Teng Y; Xu L; Yao Y; Qian W
Biomed Eng Online; 2019 Jan; 18(1):2. PubMed ID: 30602393
[TBL] [Abstract][Full Text] [Related]
11. Performance of deep learning for differentiating pancreatic diseases on contrast-enhanced magnetic resonance imaging: A preliminary study.
Gao X; Wang X
Diagn Interv Imaging; 2020 Feb; 101(2):91-100. PubMed ID: 31375430
[TBL] [Abstract][Full Text] [Related]
12. Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT.
Lee JH; Ha EJ; Kim JH
Eur Radiol; 2019 Oct; 29(10):5452-5457. PubMed ID: 30877461
[TBL] [Abstract][Full Text] [Related]
13. Differentiation of Small (≤ 4 cm) Renal Masses on Multiphase Contrast-Enhanced CT by Deep Learning.
Tanaka T; Huang Y; Marukawa Y; Tsuboi Y; Masaoka Y; Kojima K; Iguchi T; Hiraki T; Gobara H; Yanai H; Nasu Y; Kanazawa S
AJR Am J Roentgenol; 2020 Mar; 214(3):605-612. PubMed ID: 31913072
[No Abstract] [Full Text] [Related]
14. Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.
Zhao X; Qi S; Zhang B; Ma H; Qian W; Yao Y; Sun J
J Xray Sci Technol; 2019; 27(4):615-629. PubMed ID: 31227682
[TBL] [Abstract][Full Text] [Related]
15. Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study.
Taylor AG; Mielke C; Mongan J
PLoS Med; 2018 Nov; 15(11):e1002697. PubMed ID: 30457991
[TBL] [Abstract][Full Text] [Related]
16. Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.
Wu E; Hadjiiski LM; Samala RK; Chan HP; Cha KH; Richter C; Cohan RH; Caoili EM; Paramagul C; Alva A; Weizer AZ
Tomography; 2019 Mar; 5(1):201-208. PubMed ID: 30854458
[TBL] [Abstract][Full Text] [Related]
17. Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study.
Hosny A; Parmar C; Coroller TP; Grossmann P; Zeleznik R; Kumar A; Bussink J; Gillies RJ; Mak RH; Aerts HJWL
PLoS Med; 2018 Nov; 15(11):e1002711. PubMed ID: 30500819
[TBL] [Abstract][Full Text] [Related]
18. Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.
Sjoding MW; Taylor D; Motyka J; Lee E; Co I; Claar D; McSparron JI; Ansari S; Kerlin MP; Reilly JP; Shashaty MGS; Anderson BJ; Jones TK; Drebin HM; Ittner CAG; Meyer NJ; Iwashyna TJ; Ward KR; Gillies CE
Lancet Digit Health; 2021 Jun; 3(6):e340-e348. PubMed ID: 33893070
[TBL] [Abstract][Full Text] [Related]
19. Improving B-mode ultrasound diagnostic performance for focal liver lesions using deep learning: A multicentre study.
Yang Q; Wei J; Hao X; Kong D; Yu X; Jiang T; Xi J; Cai W; Luo Y; Jing X; Yang Y; Cheng Z; Wu J; Zhang H; Liao J; Zhou P; Song Y; Zhang Y; Han Z; Cheng W; Tang L; Liu F; Dou J; Zheng R; Yu J; Tian J; Liang P
EBioMedicine; 2020 Jun; 56():102777. PubMed ID: 32485640
[TBL] [Abstract][Full Text] [Related]
20. A Deep Convolutional Neural Network With Performance Comparable to Radiologists for Differentiating Between Spinal Schwannoma and Meningioma.
Maki S; Furuya T; Horikoshi T; Yokota H; Mori Y; Ota J; Kawasaki Y; Miyamoto T; Norimoto M; Okimatsu S; Shiga Y; Inage K; Orita S; Takahashi H; Suyari H; Uno T; Ohtori S
Spine (Phila Pa 1976); 2020 May; 45(10):694-700. PubMed ID: 31809468
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
