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Dr. Jeon is a member of the Cancer Epidemiology and Prevention Program of the University of Michigan Rogel Cancer Center, the Michigan Institute for Computational Discovery and Engineering, and the Institute for Healthcare Policy and Innovation. She has been a core member of large multidisciplinary national consortia: the NCI Cancer Intervention and Surveillance Modeling Network (CISNET) Lung Group, the Genetics, and Epidemiology of Colorectal Cancer Consortium (GECCO), and the Colorectal Transdisciplinary (CORECT) Study in the Genetic Associations and Mechanisms in Oncology (GAME-ON).
Dr. Jeon's research interests focus on developing models based on biological and clinical mechanisms and statistical methods to evaluate the impact of risk factors on various cancers and improve cancer outcomes. The goal of these modeling efforts is to address important practical public health and clinical questions, such as the efficacy of screening to reduce cancer incidence and mortality, and assist public health policy makers in their decision process. Particularly, my current research focuses on understanding the underlying mechanisms of the natural history of cancer, and developing innovative methodologies and computational tools to accurately predict the risk of lung cancer and colorectal cancer taking into account personal histories of environmental exposures and biological and genetic factors.
Dr. Jeon's research interests focus on developing models based on biological and clinical mechanisms and statistical methods to evaluate the impact of risk factors on various cancers and improve cancer outcomes. The goal of these modeling efforts is to address important practical public health and clinical questions, such as the efficacy of screening to reduce cancer incidence and mortality, and assist public health policy makers in their decision process. Particularly, my current research focuses on understanding the underlying mechanisms of the natural history of cancer, and developing innovative methodologies and computational tools to accurately predict the risk of lung cancer and colorectal cancer taking into account personal histories of environmental exposures and biological and genetic factors.
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Tobacco control (2023)
CANCER RESEARCH COMMUNICATIONSno. 1 (2023): 1-8
American Journal of Preventive Medicineno. 4 (2023): S53-S62
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