590 related articles for article (PubMed ID: 30972585)
1. Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.
Kim TK; Yi PH; Wei J; Shin JW; Hager G; Hui FK; Sair HI; Lin CT
J Digit Imaging; 2019 Dec; 32(6):925-930. PubMed ID: 30972585
[TBL] [Abstract][Full Text] [Related]
2. Radiology "forensics": determination of age and sex from chest radiographs using deep learning.
Yi PH; Wei J; Kim TK; Shin J; Sair HI; Hui FK; Hager GD; Lin CT
Emerg Radiol; 2021 Oct; 28(5):949-954. PubMed ID: 34089126
[TBL] [Abstract][Full Text] [Related]
3. Automated semantic labeling of pediatric musculoskeletal radiographs using deep learning.
Yi PH; Kim TK; Wei J; Shin J; Hui FK; Sair HI; Hager GD; Fritz J
Pediatr Radiol; 2019 Jul; 49(8):1066-1070. PubMed ID: 31041454
[TBL] [Abstract][Full Text] [Related]
4. Deep learning prediction of sex on chest radiographs: a potential contributor to biased algorithms.
Li D; Lin CT; Sulam J; Yi PH
Emerg Radiol; 2022 Apr; 29(2):365-370. PubMed ID: 35006495
[TBL] [Abstract][Full Text] [Related]
5. Comparison of radiologist versus natural language processing-based image annotations for deep learning system for tuberculosis screening on chest radiographs.
Yi PH; Kim TK; Lin CT
Clin Imaging; 2022 Jul; 87():34-37. PubMed ID: 35483162
[TBL] [Abstract][Full Text] [Related]
6. Lesion-aware convolutional neural network for chest radiograph classification.
Li F; Shi JX; Yan L; Wang YG; Zhang XD; Jiang MS; Wu ZZ; Zhou KQ
Clin Radiol; 2021 Feb; 76(2):155.e1-155.e14. PubMed ID: 33077154
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Generalizable Inter-Institutional Classification of Abnormal Chest Radiographs Using Efficient Convolutional Neural Networks.
Pan I; Agarwal S; Merck D
J Digit Imaging; 2019 Oct; 32(5):888-896. PubMed ID: 30838482
[TBL] [Abstract][Full Text] [Related]
9. Refining dataset curation methods for deep learning-based automated tuberculosis screening.
Kim TK; Yi PH; Hager GD; Lin CT
J Thorac Dis; 2020 Sep; 12(9):5078-5085. PubMed ID: 33145084
[TBL] [Abstract][Full Text] [Related]
10. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.
Rajpurkar P; Irvin J; Ball RL; Zhu K; Yang B; Mehta H; Duan T; Ding D; Bagul A; Langlotz CP; Patel BN; Yeom KW; Shpanskaya K; Blankenberg FG; Seekins J; Amrhein TJ; Mong DA; Halabi SS; Zucker EJ; Ng AY; Lungren MP
PLoS Med; 2018 Nov; 15(11):e1002686. PubMed ID: 30457988
[TBL] [Abstract][Full Text] [Related]
11. Can AI outperform a junior resident? Comparison of deep neural network to first-year radiology residents for identification of pneumothorax.
Yi PH; Kim TK; Yu AC; Bennett B; Eng J; Lin CT
Emerg Radiol; 2020 Aug; 27(4):367-375. PubMed ID: 32643070
[TBL] [Abstract][Full Text] [Related]
12. Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation.
Majkowska A; Mittal S; Steiner DF; Reicher JJ; McKinney SM; Duggan GE; Eswaran K; Cameron Chen PH; Liu Y; Kalidindi SR; Ding A; Corrado GS; Tse D; Shetty S
Radiology; 2020 Feb; 294(2):421-431. PubMed ID: 31793848
[TBL] [Abstract][Full Text] [Related]
13. Limited generalizability of deep learning algorithm for pediatric pneumonia classification on external data.
Xin KZ; Li D; Yi PH
Emerg Radiol; 2022 Feb; 29(1):107-113. PubMed ID: 34648114
[TBL] [Abstract][Full Text] [Related]
14. Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs.
Sim Y; Chung MJ; Kotter E; Yune S; Kim M; Do S; Han K; Kim H; Yang S; Lee DJ; Choi BW
Radiology; 2020 Jan; 294(1):199-209. PubMed ID: 31714194
[TBL] [Abstract][Full Text] [Related]
15. Performance of Deep Learning Model in Detecting Operable Lung Cancer With Chest Radiographs.
Cha MJ; Chung MJ; Lee JH; Lee KS
J Thorac Imaging; 2019 Mar; 34(2):86-91. PubMed ID: 30802232
[TBL] [Abstract][Full Text] [Related]
16. Using a Dual-Input Convolutional Neural Network for Automated Detection of Pediatric Supracondylar Fracture on Conventional Radiography.
Choi JW; Cho YJ; Lee S; Lee J; Lee S; Choi YH; Cheon JE; Ha JY
Invest Radiol; 2020 Feb; 55(2):101-110. PubMed ID: 31725064
[TBL] [Abstract][Full Text] [Related]
17. Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks.
Yi PH; Lin A; Wei J; Yu AC; Sair HI; Hui FK; Hager GD; Harvey SC
J Digit Imaging; 2019 Aug; 32(4):565-570. PubMed ID: 31197559
[TBL] [Abstract][Full Text] [Related]
18. Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents.
Wu JT; Wong KCL; Gur Y; Ansari N; Karargyris A; Sharma A; Morris M; Saboury B; Ahmad H; Boyko O; Syed A; Jadhav A; Wang H; Pillai A; Kashyap S; Moradi M; Syeda-Mahmood T
JAMA Netw Open; 2020 Oct; 3(10):e2022779. PubMed ID: 33034642
[TBL] [Abstract][Full Text] [Related]
19. Detection of COVID-19 Using Deep Learning Algorithms on Chest Radiographs.
Chiu WHK; Vardhanabhuti V; Poplavskiy D; Yu PLH; Du R; Yap AYH; Zhang S; Fong AH; Chin TW; Lee JCY; Leung ST; Lo CSY; Lui MM; Fang BXH; Ng MY; Kuo MD
J Thorac Imaging; 2020 Nov; 35(6):369-376. PubMed ID: 32969949
[TBL] [Abstract][Full Text] [Related]
20. Effect of augmented datasets on deep convolutional neural networks applied to chest radiographs.
Ogawa R; Kido T; Kido T; Mochizuki T
Clin Radiol; 2019 Sep; 74(9):697-701. PubMed ID: 31196565
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
