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Daisy Yi Ding
Daisy Yi Ding
PhD Student, Stanford University
Verified email at stanford.edu
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Cited by
Cited by
Year
Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning
P Rajpurkar, J Irvin, K Zhu, B Yang, H Mehta, T Duan, D Ding, A Bagul, ...
arXiv preprint arXiv:1711.05225, 2017
29592017
Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
P Rajpurkar, J Irvin, RL Ball, K Zhu, B Yang, H Mehta, T Duan, D Ding, ...
PLOS Medicine 15 (11), e1002686, 2018
10612018
MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs
P Rajpurkar, J Irvin, A Bagul, D Ding, T Duan, H Mehta, B Yang, K Zhu, ...
International Conference on Medical Imaging with Deep Learning (MIDL 2018), 2018
3632018
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
T Duan, A Avati, DY Ding, S Basu, AY Ng, A Schuler
International Conference on Machine Learning (ICML 2020), 2020
3102020
Handling missing data with graph representation learning
J You, X Ma, Y Ding, MJ Kochenderfer, J Leskovec
Advances in Neural Information Processing Systems (NeurIPS 2020), 2020
1452020
Learning to Summarize Radiology Findings
Y Zhang, DY Ding, T Qian, CD Manning, CP Langlotz
EMNLP 2018 Workshop on Health Text Mining and Information Analysis (EMNLP …, 2018
1402018
Counterfactual Reasoning for Fair Clinical Risk Prediction
S Pfohl, T Duan, DY Ding, NH Shah
Machine Learning for Healthcare (MLHC 2019), 2019
602019
Cooperative learning for multiview analysis
DY Ding, S Li, B Narasimhan, R Tibshirani
Proceedings of the National Academy of Sciences 119 (38), 2022
332022
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data
DY Ding, C Simpson, S Pfohl, DC Kale, K Jung, NH Shah
Pacific Symposium on Biocomputing (PSB 2019), 2018
322018
Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts
SH Strand, B Rivero-Gutiérrez, KE Houlahan, JA Seoane, LM King, ...
Cancer Cell, 2022
27*2022
Can large language models provide useful feedback on research papers? A large-scale empirical analysis
W Liang, Y Zhang, H Cao, B Wang, D Ding, X Yang, K Vodrahalli, S He, ...
arXiv preprint arXiv:2310.01783, 2023
142023
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
SL Fleming, K Jeyapragasan, T Duan, D Ding, S Gombar, N Shah, ...
NeurIPS 2019 Workshop on Machine Learning for Health (NeurIPS-ML4H 2019), 2019
42019
Multimodal Biomedical Data Fusion Using Sparse Canonical Correlation Analysis and Cooperative Learning: A Cohort Study on COVID-19
AG Er, DY Ding, B Er, M Uzun, M Cakmak, C Sadée, G Durhan, ...
2023
Machine Learning-guided Lipid Nanoparticle Design for mRNA Delivery
DY Ding, Y Zhang, Y Jia, J Sun
arXiv preprint arXiv:2308.01402, 2023
2023
Semi-supervised Cooperative Learning for Multiomics Data Fusion
DY Ding, X Shen, M Snyder, R Tibshirani
Workshop on Machine Learning for Multimodal Healthcare Data, 54-63, 2023
2023
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