Daisy Yi Ding

According to our database, Daisy Yi Ding authored at least 11 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study.

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

npj Digit. Medicine, 2024

2023

Semi-supervised Cooperative Learning for Multiomics Data Fusion.

Daisy Yi Ding, Xiaotao Shen, Michael Snyder, Robert Tibshirani

Proceedings of the Machine Learning for Multimodal Healthcare Data, 2023

2020

Handling Missing Data with Graph Representation Learning.

Jiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel J. Kochenderfer, Jure Leskovec

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

NGBoost: Natural Gradient Boosting for Probabilistic Prediction.

Tony Duan, Anand Avati, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare.

Scott L. Fleming, Kuhan Jeyapragasan, Tony Duan, Daisy Yi Ding, Saurabh Gombar, Nigam Shah, Emma Brunskill

CoRR, 2019

NGBoost: Natural Gradient Boosting for Probabilistic Prediction.

Tony Duan, Anand Avati, Daisy Yi Ding, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler

CoRR, 2019

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.

Daisy Yi Ding, Chloé Simpson, Stephen Pfohl, Dave C. Kale, Kenneth Jung, Nigam H. Shah

Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

Counterfactual Reasoning for Fair Clinical Risk Prediction.

Stephen R. Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah

Proceedings of the Machine Learning for Healthcare Conference, 2019

2018

Learning to Summarize Radiology Findings.

Yuhao Zhang, Daisy Yi Ding, Tianpei Qian, Christopher D. Manning, Curtis P. Langlotz

Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis, 2018

2017

MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs.

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

CoRR, 2017

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning.

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

CoRR, 2017