Yue Wu

发表

Estimating Retinal Sensitivity Using Optical Coherence Tomography With Deep-Learning Algorithms in Macular Telangiectasia Type 2

Aaron Y. Lee, Cecilia S Lee, Cecilia S. Lee, 2019, JAMA network open.

Exploring a Structural Basis for Delayed Rod-Mediated Dark Adaptation in Age-Related Macular Degeneration Via Deep Learning

Aaron Y. Lee, Cecilia S Lee, Cecilia S. Lee, 2020, Translational vision science & technology.

Game Theoretic Consequences of Resident Matching

Yue Wu, Yue Wu, 2020, 2003.07205.

Identifcation of The Ferroptosis-Related Gene Signature In Placenta of Patients With Early-Onset Preeclampsia

Qianghu Wang, Yue Wu, Y. Gong, 2021 .

Fully automated quantification of retinal cones and anterior chamber cells using deep learning

Aaron Y. Lee, Kathryn L. Pepple, Cecilia S Lee, 2018 .

Optic radiations representing different eccentricities age differently

Aaron Y. Lee, Cecilia S Lee, Cecilia S. Lee, 2022, bioRxiv.

Training deep learning models to work on multiple devices by cross domain learning with no additional annotations.

Aaron Y. Lee, Cecilia S Lee, C. Egan, 2022, Ophthalmology.

Forecasting future Humphrey Visual Fields using deep learning

Yue Wu, Joanne C. Wen, Philip P. Chen, 2018, bioRxiv.

Generating retinal flow maps from structural optical coherence tomography with artificial intelligence

Yue Wu, Ruikang K. Wang, Qinqin Zhang, 2018, Scientific Reports.

Deep-Learning Based, Automated Segmentation of Macular Edema in Optical Coherence Tomography

Yue Wu, Ariel Rokem, Aaron Y. Lee, 2017, bioRxiv.

Foveal Curvature and Its Associations in UK Biobank Participants

A. Rudnicka, K. Williams, C. Egan, 2022, Investigative ophthalmology & visual science.

Fully automated, deep learning segmentation of oxygen-induced retinopathy images.

Ariel Rokem, Aaron Y. Lee, Cecilia S Lee, 2017, JCI insight.

Specific and non-linear effects of glaucoma on optic radiation tissue properties

Aaron Y. Lee, Adam C. Richie-Halford, Cecilia S Lee, 2023, bioRxiv.

De Novo Identification and Visualization of Important Cell Populations for Classic Hodgkin Lymphoma Using Flow Cytometry and Machine Learning.

Aaron Y. Lee, David Wu, P. Simonson, 2021, American journal of clinical pathology.

Disparities in delivery of ophthalmic care; An exploration of public Medicare data

Aaron Y. Lee, Aaron Y Lee, Doug M. Baughman, 2017, PloS one.

Deep-Learning Based, Automated Segmentation of Macular Edema in Optical Coherence Tomography

Yue Wu, Ariel Rokem, Aaron Y. Lee, 2017, bioRxiv.

Assessment of the need for separate test set and number of medical images necessary for deep learning: a sub-sampling study

Ariel Rokem, Yue Wu, Aarom Y Lee, 2017, bioRxiv.

Development and validation of a machine learning, smartphone-based tonometer

Philip P. Chen, Aaron Y. Lee, J. Wen, 2019, British Journal of Ophthalmology.

Automated Machine Learning Pipeline for Predicting Retinal Sensitivity from Optical Coherence Tomography in Macular Telangiectasia Type 2

Aaron Y. Lee, Cecilia S. Lee, Catherine A Egan, 2019 .

Generating retinal flow maps from structural optical coherence tomography with artificial intelligence

Ruikang K. Wang, Aaron Y. Lee, Ariel J. Tyring, 2018, bioRxiv.

Machine Learning Prediction of Non-Coding Variant Impact in Human Retinal cis-Regulatory Elements

Aaron Y. Lee, T. Cherry, A. Timms, 2021, bioRxiv.

Glaucoma visual field quantification with eye tracker

Menghan Hu, Yue Wu, Jingyu Tang, 2023, Displays.

MRI2MRI: A deep convolutional network that accurately transforms between brain MRI contrasts

Ariel Rokem, Aaron Y. Lee, Sa Xiao, 2018, bioRxiv.

Generating retinal flow maps from structural optical coherence tomography with artificial intelligence

Aaron Y. Lee, Ariel J. Tyring, Nicolaas P. Deruyter, 2018, bioRxiv.