Dr. Suresh is a Research Assistant Professor in the Department of Radiation Oncology. She received her MMath in Biostatistics from the University of Waterloo, and her PhD in Biostatistics from the University of Michigan. Her research interests include survival analysis, longitudinal data, joint modeling, and prediction models, with applications in cancer research and other health outcomes.
Areas of Interest
- Developing prediction models for personalized medicine
- Statistical analysis of outcomes in cancer research
- Pragmatic trial design and analysis
- 2018-2022 Research Assistant Professor of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus
Published Articles or Reviews
- Dess, R.T., Suresh, K., Zelefsky, M.J., Freedland, S.J., Mahal, B.A., Cooperberg, M.R., Davis, B.J., Horwitz, E.M., Terris, M.K., Amling, C.L. and Aronson, W.J., 2020. Development and Validation of a Clinical Prognostic Stage Group System for Nonmetastatic Prostate Cancer Using Disease-Specific Mortality Results From the International Staging Collaboration for Cancer of the Prostate. JAMA oncology, 6(12), 1912-1920.
- Suresh, K., Taylor, J.M.G. and Tsodikov, A., 2021. A copula‐based approach for dynamic prediction of survival with a binary time‐dependent covariate. Statistics in Medicine. 40(23), 4931-4946.
- Suresh, K., Taylor, J.M.G. and Tsodikov, A., 2021. A Gaussian copula approach for dynamic prediction of survival with a longitudinal biomarker. Biostatistics, 22(3), 504-521.
- Pickett, K.L., Suresh, K., Campbell, K.R., Davis, S. and Juarez-Colunga, E., 2021. Random survival forests for dynamic predictions of a time-to-event outcome using a longitudinal biomarker. BMC medical research methodology, 21(1), pp.1-14.
- Suresh, K., Holtrop, J.S., Dickinson, L.M., Willems, E., Smith, P.C., Gritz, R.M. and Perreault, L., 2022. PATHWEIGH, pragmatic weight management in adult patients in primary care in Colorado, USA: study protocol for a stepped wedge cluster randomized trial. Trials, 23(1), pp.1-14.
- Severn, C., Suresh, K., Görg, C., Choi, Y.S., Jain, R. and Ghosh, D., 2022. A Pipeline for the Implementation and Visualization of Explainable Machine Learning for Medical Imaging Using Radiomics Features. Sensors, 22(14), p.5205.
- Suresh, K., Severn, C. and Ghosh, D., 2022. Survival prediction models: an introduction to discrete-time modeling. BMC Medical Research Methodology, 22(1), pp.1-18.