Daisy Yi Ding

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Medförfattare

Pranav RajpurkarAssistant Professor of Biomedical Informatics, Harvard Medical SchoolVerifierad e-postadress på hms.harvard.edu
Andrew NgStanford UniversityVerifierad e-postadress på cs.stanford.edu
Tony DuanStanford UniversityVerifierad e-postadress på cs.stanford.edu
Curtis P. LanglotzProfessor of Radiology, Medicine, and Biomedical Data Science, Stanford UniversityVerifierad e-postadress på stanford.edu
Robert TibshiraniProfessor of Biomedical Data Sciences, and of Statistics, Stanford UniversityVerifierad e-postadress på stanford.edu
Nigam ShahProfessor of Medicine, and Biomedical Data Science, Stanford UniversityVerifierad e-postadress på stanford.edu
Alejandro SchulerAssistant Professor, UC BerkeleyVerifierad e-postadress på berkeley.edu
Stephen R. PfohlGoogleVerifierad e-postadress på google.com
Jiaxuan YouAssistant Professor, UIUC CSVerifierad e-postadress på cs.stanford.edu
Jure LeskovecProfessor of Computer Science, Stanford UniversityVerifierad e-postadress på cs.stanford.edu
Mykel J. KochenderferAssociate Professor, Stanford UniversityVerifierad e-postadress på stanford.edu
Christopher D ManningProfessor of Computer Science and Linguistics, Stanford UniversityVerifierad e-postadress på stanford.edu
Yuhao ZhangScientist/Engineer @ Samaya AIVerifierad e-postadress på samaya.ai
Shuangning LiUniversity of ChicagoVerifierad e-postadress på chicagobooth.edu
Balasubramanian NarasimhanSenior Research Scientist, Department of Biomedical Data Sciences and Department of StatisticsVerifierad e-postadress på stanford.edu

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Daisy Yi Ding

PhD Student, Stanford University

Verifierad e-postadress på stanford.edu


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
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	3577	2017
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	1310	2018
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	461	2020
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	387	2018
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	218	2020
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	169	2018
Can large language models provide useful feedback on research papers? A large-scale empirical analysis W Liang, Y Zhang, H Cao, B Wang, DY Ding, X Yang, K Vodrahalli, S He, ... NEJM AI, 2024	113	2024
Counterfactual Reasoning for Fair Clinical Risk Prediction S Pfohl, T Duan, DY Ding, NH Shah Machine Learning for Healthcare (MLHC 2019), 2019	80	2019
Cooperative learning for multiview analysis DY Ding, S Li, B Narasimhan, R Tibshirani Proceedings of the National Academy of Sciences 119 (38), 2022	57	2022
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	52	2022
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	32	2018
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	7	2019
Machine Learning-guided Lipid Nanoparticle Design for mRNA Delivery DY Ding, Y Zhang, Y Jia, J Sun ICML CompBio Workshop, 2023	6	2023
Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study AG Er, DY Ding, B Er, M Uzun, M Cakmak, C Sadee, G Durhan, ... npj Digital Medicine 7 (1), 117, 2024	3	2024
Semi-supervised Cooperative Learning for Multiomics Data Fusion DY Ding, X Shen, M Snyder, R Tibshirani ICML Workshop on Machine Learning for Multimodal Healthcare Data, 54-63, 2023	1	2023
Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition NF Greenwald, I Nederlof, C Sowers, D Ding, S Park, A Kong, K Houlahan, ... bioRxiv, 2025.01. 26.634557, 2025		2025
CoCA: Cooperative Component Analysis DY Ding, A Green, MW Sun, R Tibshirani arXiv preprint arXiv:2407.16870, 2024		2024

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