Yuan Chen, PhD

Assistant Attending Biostatistician
Epidemiology & Biostatistics
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Yuan Chen, PhD

Assistant Attending Biostatistician
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Yuan Chen

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[email protected]

Education

Columbia University

Current Research Interest

Dr. Chen’s main research interest lies in developing statistical and machine learning methods to facilitate precision medicine, which tailors treatments based on individual patient characteristics. She has developed methods to integrate evidence from various data domains and sources, effectively addressing patient heterogeneity and studying personalized treatment strategies to enhance treatment responses and patient outcomes. She has also developed methods for studying dynamic treatment regimes to improve recurrent disease management using clinical trial data and observational databases. Recently, she works on the AACR Project GENIE BPC to integrate and harmonize multi-institutional genomic data to promote precision oncology. Dr. Chen collaborates with investigators in the Breast Medicine Service for the design and analysis of retrospective and prospective studies.

Publications

Selected peer-reviewed publications:

  1. Xu. T., Chen, Y., Zeng D., & Wang, Y. (2023). Mixed-Response State-Space Model for Analyzing Multi-Dimensional Digital Phenotypes, Journal of the American Statistical Association, DOI: 10.1080/01621459.2023.2225742
  2. Chen, Y., Zeng, D., & Wang, Y. (2021). Learning individualized treatment rules for multiple-domain latent outcomes. Journal of the American Statistical Association, 116(533), 269–282.
  3. Chen, Y., Fei, W., Qinxia, W., Zeng, D., & Wang, Y. (2021). Dynamic COVID risk assessment accounting
    for community virus exposure from a spatial-temporal transmission model. Advances in Neural
    Information Processing Systems (NeurIPS), 34.
  4. Chen, Y., Wang, Y., & Zeng, D. (2020). Synthesizing independent stagewise trials for optimal dynamic treatment regimes. Statistics in Medicine, 39(28), 4107–4119. 
  5. Chen, Y., Zeng, D., Xu, T., & Wang, Y. (2020). Representation learning for integrating multi-domain outcomes to optimize individualized treatment. Advances in Neural Information Processing Systems (NeurIPS),33.

Disclosures

Doctors and faculty members often work with pharmaceutical, device, biotechnology, and life sciences companies, and other organizations outside of MSK, to find safe and effective cancer treatments, to improve patient care, and to educate the health care community.

MSK requires doctors and faculty members to report (“disclose”) the relationships and financial interests they have with external entities. As a commitment to transparency with our community, we make that information available to the public.

Yuan Chen discloses the following relationships and financial interests:

No disclosures meeting criteria for time period


The information published here is for a specific annual disclosure period. There may be differences between information on this and other public sites as a result of different reporting periods and/or the various ways relationships and financial interests are categorized by organizations that publish such data.

This page and data include information for a specific MSK annual disclosure period (January 1, 2022 through disclosure submission in spring 2023). This data reflects interests that may or may not still exist. This data is updated annually.

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