معرفی
Dr. Chuan Hong is an Assistant Professor of Biostatistics & Bioinformatics at Duke University School of Medicine and a member of the Duke Clinical Research Institute (DCRI) and Biostatistics, Epidemiology, and Research Design (BERD) Methods Core. With a PhD in Biostatistics from the University of Texas Health Science Center at Houston, she completed postdoctoral training in Biostatistics at Harvard T.H. Chan School of Public Health (2016-2018) and Biomedical Informatics at Harvard Medical School (2018-2019).
- PhD, Biostatistics - University of Texas Health Sciences Center, Houston (2016)
- Postdoctoral Training - Harvard T.H. Chan School of Public Health (2016-2018)
- Postdoctoral Training - Harvard Medical School (2018-2019)
Her research focuses on integrating machine learning with clinical data science to address critical healthcare challenges. Key areas include algorithmic fairness, cardiovascular risk prediction for women with adverse pregnancy outcomes, equitable pulse oximetry, and privacy-preserving federated learning techniques for multi-site EHR analysis. She leads NIH-funded projects on stroke risk prediction and Long COVID phenotyping, while exploring generative AI applications in clinical workflows.
Recent publications highlight her methodological innovations in federated learning (FairFML, FedIMPUTE), domain-specific pretraining for medical imaging, and AI evaluation frameworks for healthcare communication. Her work bridges statistical rigor with practical clinical informatics solutions, particularly in debiasing clinical algorithms and optimizing health data infrastructure.
- NIH Grant: Overcoming inequities in Pulse oximetry Through clinical InformatiCs (2025-2029)
- Brigham & Women's Hospital Grant: Machine Learning for CVD Risk Prediction in Women (2023-2027)
- American Heart Association Grant: Debiasing Clinical Care Algorithms (2024-2025)
- Harvard/VA Subcontract: MAVERIC Project (2024-2025)
- NIH Grant: Stroke Risk Prediction with Machine Learning (2020-2025)
