Joint Institution Seminar Series

Joint Institution Seminar Series

The Biostatistics, Epidemiology, and Research Design (BERD) groups at Duke, UNC, and Wake Forest are all supported by the Clinical and Translational Science Award and have teamed together to share educational and training materials. The following seminars will be shared across all three institutions for Fall 2021.

Experimental Study Design

Wednesday, October 6th, 12pm-1pm EST

Registration: https://redcap.wakehealth.edu/redcap/surveys/?s=PNYYDXKNAR

Mike Bancks, MPH, PhD
Assistant Professor of Epidemiology and Prevention
Wake Forest School of Medicine

This session provides an overview of the experimental study design and fundamental concepts including randomization, equipoise, and masking.

Level/audience: Clinical and translational researchers who have basic quantitative training in biostatistical methods

 

Neural Networks for Survival Outcomes Applied to Medical Images

Friday, October 8, 2021, 1:30-2:30pm EST

https://duke.zoom.us/j/99770256430?pwd=bUNQWllGdVVjM2l1TmRxR0dZdFBsQT09

Samantha Morrison, PhD
Biostatistician III
BERD Methods Core

Neural networks have become widely used for development of risk prediction models. In particular, convolutional neural networks offer a promising method for incorporating imaging data into risk prediction models.  However, these algorithms cannot be directly applied to situations of incomplete outcome data which poses a problem for development of risk prediction models for survival outcomes.  Standard neural networks build prediction models through estimating an unknown weight vector by minimizing a loss function.  To account for censored data, we proposed an extension to these algorithms that replaces the standard loss function with censoring unbiased loss functions. 

In this talk, we provide background on neural networks for imaging data.  Then, we discuss the methodological and practical complications associated with using convolutional neural networks for censored data.  We propose our censoring unbiased loss functions and illustrate the performance through an analysis of a histology dataset of gliomas.

Level/audience: Applied biostatisticians

 

Observational Study Designs

Wednesday, November 3rd, 12pm-1pm EST

Registration: https://redcap.wakehealth.edu/redcap/surveys/?s=74X3JFYEL8DW34JA

Mike Bancks, MPH, PhD
Assistant Professor of Epidemiology and Prevention
Wake Forest School of Medicine

This introductory-level session will provide an overview of the fundamental observational study designs used in clinical and epidemiological research.

Level/audience: Clinical and translational researchers who have basic quantitative training in biostatistical methods

 

Biostatistics Seminar Series: Causal inference with observational data: A gentle introduction

Friday, November 05, 2021, 10:30 am - 12:00 pm

Registration: http://apps2.research.unc.edu/events/index.cfm?event=events.go&key=AD2E

Michael Hudgens, PhD
Professor and Associate Chair, Department of Biostatistics
Gillings School of Global Public Health, UNC-Chapel Hill

Biomedical researchers often want to answer causal questions, but they often have access to observational data, not clinical trials. In this session of the TraCS Biostatistics Seminar series, you’ll learn why causal inference is difficult with observational data and what can be done to allow for valid causal inferences if you have observational data.

Level/audience: Clinical and translational researchers who have basic quantitative training in biostatistical methods

 

Getting Started on Literature Reviews

Wednesday, November 17th, 12pm-1pm EST

Registration: https://redcap.wakehealth.edu/redcap/surveys/?s=H8PWFAA3R47WTWXJ

Brandy W. Hardy
Acquisitions and e-Resource Librarian
Wake Forest School of Medicine

The goal of this session is be to provide a balance of beginner and intermediate-level skills and resources (both general and local) for researchers when undertaking a literature review.

Level/audience: Clinical and translational researchers

 

Tips for Effective Data Visualization

Friday, December 10, 2021, 1:30-2:30pm EST

Registration: https://duke.zoom.us/j/94919731322?pwd=aE15bFZMQWFkZzlOc2N0WmdCUWR0UT09

Eric E Monson, PhD
Data Visualization Specialist
Duke Libraries Center for Data and Visualization Sciences

Visualization is a powerful way to reveal patterns in data, attract attention, and get your message across to an audience quickly and clearly. But, there are many steps in that journey from exploration to information to influence, and many choices to make when putting it all together to tell your story. I will cover some basic guidelines for effective visualization, point out a few common pitfalls to avoid, and run through a critique and iterations of an existing visualization to help you start seeing better choices beyond the program defaults.

Level/audience: Applied biostatisticians, statistics for clinicians