Differences

This shows you the differences between two versions of the page.

--- seminars:datasci:021423 [2023/02/03 20:34] – created gfu
+++ seminars:datasci:021423 [2023/02/03 20:35] (current) – gfu
@@ Line 1: / Line 1: @@
+<WRAP centeralign>##Data Science Seminar##\\ Hosted by the Department of Mathematics and Statistics</WRAP>
+  * Date: Tuesday, February 14, 2023
+  * Time: 12:00pm -- 1:00pm
+  * Room: Whitney Hall 100E
+  * Speaker: Dr. Yuan Fang  (Binghamton University)
+  * Title: Clustering disease trajectories: statistical method applications and evaluation.
+<WRAP center box 80%>
+<WRAP centeralign>**//Abstract//**</WRAP>
+\\
+Biological and medical data increasingly have high dimensionality and complicated
+structures. Cluster analysis is a common exploratory analysis technique for identifying
+the underlying latent classes in a dataset. For many diseases, the underlying
+pathophysiology is complex, and heterogeneity in the natural history of the disease is
+common. Clustering the trajectories of disease progression can be helpful in
+understanding observed variability. In this talk, I will discuss the applications and
+evaluation of cluster analysis for identifying heterogeneity in longitudinal trajectories
+using a latent class mixed effect model (LCMM) approach. I will start with two examples
+of applying LCMM to identify latent patterns in trajectories: a) We have successfully
+applied LCMM and identified clinically meaningful subgroups in the disease progression
+of Duchenne muscular dystrophy; b) I will present preliminary results from our current
+study on the heterogeneity in trajectories of cognitive status, measured by a more
+complex outcome set, in participants from the community-based Framingham Heart
+Study. Then, I will show how to use simulation studies to evaluate the ability of LCMMs
+to accurately classify individuals for a wide range of noise and variability in trajectories
+and to provide guidelines for model specification when using this technique.
+ \\
+Biography of the speaker: Dr. Fang joined the Department of Pharmaceutical Sciences at Binghamton University in 2023. She received her Ph.D. in Mathematics and Statistics with a focus on Statistics from Binghamton University Department of Mathematical Sciences under the guidance of Dr. Sanjeena Dang. Her Ph.D. research
+mainly focused on developing novel unsupervised learning algorithms for non-standard data types that
+are usually encountered in biomedical research. Following her graduate studies, Yuan joined the group
+of Drs. Kathryn Lunetta and Joanne Murabito at Boston University School of Public Health as a
+postdoctoral associate. Her postdoc research focused on applying statistical tools to investigate the
+association between circulating immune cell phenotypes in the pro-inflammatory and regulatory
+pathways with cognitive decline, dementia, and Alzheimer’s disease. She has also been working on
+quantifying the heterogeneity in decline trajectories of cognitive functions in the Framingham Heart
+Study participants. Yuan’s current research focuses on studying lipid profiles for ceramide pathways in
+boys with Duchenne Muscular Dystrophy using multi-omics statistical and bioinformatics approaches.
+She is also interested in extending existing models and statistical approaches to clustering omics data
+and longitudinal data.
+</WRAP>