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ORCIDDaisy Yi Ding
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2020 – today
- 2024
[j1]Ahmet Gorkem Er
, Daisy Yi Ding, Berrin Er, Mertcan Uzun, Mehmet Cakmak, Christoph Sadee, Gamze Durhan, Mustafa Nasuh Ozmen, Mine Durusu Tanriover, Arzu Topeli, Yesim Aydin Son, Robert Tibshirani, Serhat Unal, Olivier Gevaert:
Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study. npj Digit. Medicine 7(1) (2024)- 2023
- [c6]Daisy Yi Ding, Xiaotao Shen, Michael Snyder, Robert Tibshirani:
Semi-supervised Cooperative Learning for Multiomics Data Fusion. ML4MHD 2023: 54-63 - 2020
- [c5]Tony Duan, Anand Avati, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler:
NGBoost: Natural Gradient Boosting for Probabilistic Prediction. ICML 2020: 2690-2700 - [c4]Jiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel J. Kochenderfer, Jure Leskovec:
Handling Missing Data with Graph Representation Learning. NeurIPS 2020 - [i8]Jiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel J. Kochenderfer, Jure Leskovec:
Handling Missing Data with Graph Representation Learning. CoRR abs/2010.16418 (2020)
2010 – 2019
- 2019
- [c3]Stephen R. Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah:
Counterfactual Reasoning for Fair Clinical Risk Prediction. MLHC 2019: 325-358 - [c2]Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah:
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. PSB 2019: 18-29 - [i7]Stephen Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah:
Counterfactual Reasoning for Fair Clinical Risk Prediction. CoRR abs/1907.06260 (2019) - [i6]Tony Duan, Anand Avati, Daisy Yi Ding, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler:
NGBoost: Natural Gradient Boosting for Probabilistic Prediction. CoRR abs/1910.03225 (2019) - [i5]Scott L. Fleming, Kuhan Jeyapragasan, Tony Duan, Daisy Yi Ding, Saurabh Gombar, Nigam Shah, Emma Brunskill:
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare. CoRR abs/1911.07084 (2019) - 2018
- [c1]Yuhao Zhang, Daisy Yi Ding, Tianpei Qian, Christopher D. Manning, Curtis P. Langlotz:
Learning to Summarize Radiology Findings. Louhi@EMNLP 2018: 204-213 - [i4]Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah:
The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data. CoRR abs/1808.03331 (2018) - [i3]Yuhao Zhang, Daisy Yi Ding, Tianpei Qian, Christopher D. Manning, Curtis P. Langlotz:
Learning to Summarize Radiology Findings. CoRR abs/1809.04698 (2018) - 2017
- [i2]Pranav Rajpurkar, Jeremy Irvin, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Yi Ding, Aarti Bagul, Curtis P. Langlotz, Katie S. Shpanskaya, Matthew P. Lungren, Andrew Y. Ng:
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. CoRR abs/1711.05225 (2017) - [i1]Pranav Rajpurkar, Jeremy Irvin, Aarti Bagul, Daisy Yi Ding, Tony Duan, Hershel Mehta, Brandon Yang, Kaylie Zhu, Dillon Laird, Robyn L. Ball, Curtis P. Langlotz, Katie S. Shpanskaya, Matthew P. Lungren, Andrew Y. Ng:
MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs. CoRR abs/1712.06957 (2017)
Coauthor Index
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last updated on 2024-09-10 01:07 CEST by the dblp team
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