Speaker Profile

Ph.D., Vice Dean for Data Science and Information Technology, Duke University School of Medicine

Dr. Michael Pencina is a Professor of Biostatistics and Bioinformatics and Vice Dean for Data Science and Information Technology for the Duke University School of Medicine. He is a senior member of the dean’s leadership team, responsible for developing and implementing quantitative science strategies as they pertain to the education and training, and laboratory, clinical science, and data science missions of the Duke School of Medicine. Previously, Dr. Pencina served as the director of Biostatistics at Duke Clinical Research Institute (DCRI). He is an internationally recognized expert in risk prediction model development and evaluation. The methods for quantifying improvement in model performance proposed in his research have been recommended by expert panels and guideline groups. Dr. Pencina is actively involved in the design, conduct and analysis of clinical studies with particular focus on novel and efficient designs and applications of machine learning for medical decision support. Dr. Pencina has co-authored over 300 manuscripts in peer-reviewed journals and has been recognized multiple times as a Thomson Reuters Highly Cited Researcher. He serves as deputy editor for Statistics at JAMA-Cardiology and associate editor for Statistics in Medicine.


Fusion of Quantitative Methods to Support Learning
Quantitative methods have a key role to play as we embark on a mission to make learning health system a reality. We illustrate how a fusion of machine learning and biostatistics in the context of a team science approach can lead to meaningful progress beyond what each discipline can accomplish on its own.

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