Seminar Series

The Applied Biostatistics Seminar Series consists of a series of talks with the primary purpose of furthering statistical knowledge on an applied level. Talks will focus on advances in biostatistical methods and statistical programming techniques and their translation into addressing biomedical research questions. The seminars are open to all members of the Duke community, but primarily geared toward applied statistical researchers.

Genetics and Genomics of Human Gene Regulation

Tim Reddy, PhD
Wednesday, May 3, 2017 - 11:00 at MSRB I, Room #001, 203 Research Drive

My long-term goal is to understand how changes in gene regulation contributes to human diseases. Progress towards that goal is important for ultimately improving the prevention, diagnosis, and treatment of many diseases, and could therefore benefit billions of people worldwide. A leading hypothesis is that the genetic contributions to many...
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Integrative Analysis for Incorporating the Microbiome to Improve Precision Medicine

Hongzhe Li
Monday, April 24, 2017 - 12:00 at Hock Plaza, 2nd Floor, CRTP Classroom

The gut microbiome impacts health and risk of disease by dynamically integrating signals from the host and its environment. High throughput sequencing technologies enable individualized characterization of the microbiome composition and function. The resulting data can potentially be used for personalized diagnostic assessment, risk stratification, disease prevention and treatment. In...
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The Risky Business of Odds Ratios: Misuses and Misinterpretations

Biostat Core Tutorial
Friday, April 21, 2017 - 01:30 at Hock Plaza 11025

Binary outcomes arise in many different settings under a variety of study designs. Some examples include whether or not a disease is cured in a randomized controlled trial of a drug, and case or control status in a case-control study. The relative risk (i.e., risk ratio) and the odds ratio...
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Interpretable Machine Learning to Deconstruct the Neural Basis of Psychiatric Disorders

Tuesday, February 28, 2017 - 12:00 at Hock Plaza - 2nd Floor CRTP Classroom

There is an extensive literature in machine learning demonstrating extraordinary ability to predict labels based off an abundance of data, such as object and voice recognition. Multiple scientific domains are poised to go through a data revolution, in which the quantity and quality of data will increase dramatically over the...
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Flexible Modeling for Optimal Treatment Regime Estimation in Complex Disease Studies

Friday, February 24, 2017 - 01:15 at Hock Plaza 8th Floor #8065

Developing personalized treatment regimes has become more and more popular in clinical studies. A good treatment decision rule could greatly facilitate the improvement of patient care while limiting the demand for resources. Causal inference methods play an important role in estimating such rules, especially in connecting observational data to regime...
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