Event Calendar

MHRI-GHUCCTS Monthly Statistical Seminar Series: Fractional Polynomial Regression

Date	Fri, Feb 21
Time	12: 00 PM - 1: 00 PM
Location	Zoom

This month's MHRI-GHUCCTS Monthly Statistical Seminar Series will be held Friday, February 21, 2025, from 12 PM - 1 PM. This series features Dr. Paul Kolm, Associate Director in the Center for Biostatistics, Informatics, & Data Science (CBIDS) at MedStar Health Research Institute.

The topic of this month's seminar will be on how linear regression is defined by an intercept and slope of a straight line (i.e., constant slope) describing the relationship between 2 variables. In some cases, however, the relationship is non-linear (slope is not constant). We will discuss both integer and fractional polynomial regression for assessing non-linear relationships.

Upcoming Events

Mar 12

Virtual Applied Data Science Training Institute (VADSTI) 2025 Training Series: Module 4 - Seminal Presentation on Current Development in Data Science Mar 12, 2025 5: 00 PM - 8: 00 PM Zoom

This free Spring Training Series will cover topics including, Foundations of Data Science, Introduction to Python, Basic Statistical Concepts, Data Exploration & Visualization, Experimentation in Data Science, and introduction to algorithmic techniques in Machine Learning.

Mar 14

Clinical and Translational Research Grand Rounds:“Safe Babies Safe Moms: Redesigning Maternal & Infant Healthcare in DC with a multigenerational model that reduces health disparities” Mar 14, 2025 12: 00 PM - 1: 00 PM Virtual via Zoom

Mar 19

Virtual Applied Data Science Training Institute (VADSTI) 2025 Training Series: Module 5 - Introduction to Machine Learning I Mar 19, 2025 5: 00 PM - 8: 00 PM Zoom

Mar 20

The Intersection of Ethics, Data Science, Informatics, and Epidemiology Mar 20, 2025 10: 00 AM - 2: 00 PM Zoom

This symposium explores how experts from different fields—ethics, data science, informatics, and epidemiology—work together to make sure health data are used responsibly. We will discuss real-world challenges like protecting people’s privacy, getting consent before using personal data, and ensuring that health decisions are fair for all communities, especially those who have been—and continue to be—underrepresented, underprivileged, or underserved (the "triple Us").