Statistical and Computational Approaches Towards Understanding Age-related Macular Degeneration and Its Progression

Seminar Series

Friday, February 7, 2020 - 10:00
Hock Plaza, 8th Floor #8065
Wei Chen, PhD

Age-related Macular Degeneration (AMD) is a multifactorial irreversible retina disease and the leading cause of blindness in the developed world. Multiple factors including aging, genetics, and smoking are associated with AMD development and its progression. In this talk, I will discuss recent novel developments in addressing several key statistical issues and challenges from our long-term study of AMD using large-scale genetic and fundus image data. These methods include (1) efficient copula-based score test and analysis for bivariate time-to-event data, (2) gene-based association analysis for bivariate time-to-event data through functional regression with copula models, and (3) deep-learning-based prediction methods for AMD development and progression. We show that statistical and computational approaches are critical in understanding AMD pathogenesis and predicting disease progression, particularly in the era of big data.

Wei Chen, PhD
Associate Professor 
Pediatrics

Director 
Statistical Genetics Core
Division of Pediatric Pulmonology
Department of Pediatrics

UPMC Children’s Hospital of Pittsburgh
University of Pittsburgh