Kim, Eunhee

Assistant Professor of Biostatistics

Department of Biostatistics and Center for Statistical Sciences
Brown University
Box G-S121-7
121 S. Main Street
Providence, RI 02912
Phone:+1 401 863 9968
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Eunhee Kim, PhD, is an Assistant Professor of Biostatistics at Brown. Her methodological research interests include semiparametric and nonparametric methods for evaluating biomarkers and medical diagnostic tests; classification and prediction methods; and longitudinal data analysis.
Her current collaborative research interests lie in cancer, maternal and child health, and women's health. She is a lead statistician of the American College of Radiology Imaging Network (ACRIN), conducting clinical research to evaluate diagnostic imaging and image-guided therapy for cancer.
Dr. Kim currently teaches Linear and Generalized Linear Models, Advanced Methods for Multivariate Analysis, and Longitudinal Data Analysis in the Department of Biostatistics.


My broad methodological research interest lies in statistical methods in diagnostic medicine, classification and prediction methods, and longitudinal data analysis.
Biomarker evaluation, classification and prediction, longitudinal data analysis: My first research focus is the statistical evaluation of biomarkers and diagnostic tests for disease classification and prediction.
I am interested in developing statistical methods that integrate multiple biomarkers, noting that different biomarkers can provide unique insights into disease mechanisms and newly discovered biomarkers can provide additional information for a specific disease. Motivated by this idea, I have developed semi-parametric transformation models that combine multiple biomarkers, possibly with detection limits.
In recent years, my primary research interest has evolved into modeling longitudinal or repeatedly measured biomarkers in the follow-up study. Specifically, I have researched statistical methods to integrate longitudinally progressed biomarkers for evaluating treatment response. In this research, I aim to develop clinically meaningful measures to determine the effectiveness of using longitudinal biomarkers, which will enable a more robust assessment of treatment response.
Statistical methods in diagnostic medicine: Given the recent technological advances in digital radiological imaging systems, numerous studies have sought to investigate whether new techniques provide a diagnostic performance superior to that of conventional imaging techniques. My second primary research interest focuses on developing statistical methods to assess and compare diagnostic techniques accommodating a particular situation or a study design.


Ph.D. (Biostatistics), University of North Carolina at Chapel Hill, 2009


David P. Byar Young Investigator Travel Award, Biometrics Section, American Statistical Association, 2010
Richard B. Salomon Faculty Research Award, Brown University, 2012


I teach graduate-level advanced biostatistics courses:
PHP2540 Advanced Methods for Multivariate Analysis (Spring 2011-Present)
PHP2601 Linear and Generalized Linear Models (Fall 2009-Present)
PHP2603 Longitudinal Data Analysis (Spring 2010-Present)


Protocol Statistician, Biostatistics and Data Management Center of the American College of Radiology Imaging Network (ACRIN), 2009 to Present
- The ACRIN is a national cooperative group, organized and funded by the National Cancer Institute in 1999 to conduct multi-center, interdisciplinary clinical evaluations of diagnostic imaging in the early detection and diagnosis, staging, and treatment of cancer. ACRIN's ultimate goal is to develop and disseminate scientific knowledge that will help reduce cancer-related mortality and morbidity and improve the quality of life of cancer patients.
Key Projects:
ACRIN 6698: MR Imaging Biomarkers for Assessment of Breast Cancer Response to Neoadjuvant Treatment: A sub-study of the I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis) (Role: Lead Statistician)
ACRIN 6701: Repeatability Assessment of Quantitative DCE-MRI and DWI: A Multicenter Study of Functional Imaging Standardization in the Prostate (Role: Lead Statistician)
ECOG 1412: Randomized Phase II Study of Lenalidomide R-CHOP (R2CHOP) vs RCHOP (Rituximab, Cyclophosphamide, Doxorubicin, Vincristine and Prednisone) in Patients with Newly Diagnosed Diffuse Large B Cell Lymphoma (Role: Imaging Statistician)


Curriculum Vitae

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