 Connection
Fuyong Xing to Machine Learning
This is a "connection" page, showing publications Fuyong Xing has written about Machine Learning.
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Connection Strength |
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0.686 |
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Xing F, Yang L. Fast Cell Segmentation Using Scalable Sparse Manifold Learning and Affine Transform-approximated Active Contour. Med Image Comput Comput Assist Interv. 2015 Oct; 9351:332-339.
Score: 0.348
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Tiwari P, Colborn KL, Smith DE, Xing F, Ghosh D, Rosenberg MA. Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation. JAMA Netw Open. 2020 01 03; 3(1):e1919396.
Score: 0.116
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Xing F, Shi X, Zhang Z, Cai J, Xie Y, Yang L. Transfer Shape Modeling Towards High-throughput Microscopy Image Segmentation. Med Image Comput Comput Assist Interv. 2016 Oct; 9902:183-190.
Score: 0.092
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Warsavage T, Xing F, Bar?n AE, Feser WJ, Hirsch E, Miller YE, Malkoski S, Wolf HJ, Wilson DO, Ghosh D. Quantifying the incremental value of deep learning: Application to lung nodule detection. PLoS One. 2020; 15(4):e0231468.
Score: 0.030
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Shi X, Su H, Xing F, Liang Y, Qu G, Yang L. Graph temporal ensembling based semi-supervised convolutional neural network with noisy labels for histopathology image analysis. Med Image Anal. 2020 02; 60:101624.
Score: 0.029
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Jensen AM, Tregellas JR, Sutton B, Xing F, Ghosh D. Kernel machine tests of association between brain networks and phenotypes. PLoS One. 2019; 14(3):e0199340.
Score: 0.027
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Su H, Xing F, Yang L. Robust Cell Detection of Histopathological Brain Tumor Images Using Sparse Reconstruction and Adaptive Dictionary Selection. IEEE Trans Med Imaging. 2016 06; 35(6):1575-86.
Score: 0.022
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Su H, Xing F, Kong X, Xie Y, Zhang S, Yang L. Robust Cell Detection and Segmentation in Histopathological Images Using Sparse Reconstruction and Stacked Denoising Autoencoders. Med Image Comput Comput Assist Interv. 2015 Oct; 9351:383-390.
Score: 0.022
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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