Biomedical Data Science

BMED-4265

Introduction of multivariate statistical methods to model and analyze recorded data from physiological systems in biomedical engineering. Statistical approaches related to applied multivariate statistics, classification and regression. Associated linear methods include principal component analysis, Fisher discriminant analysis, partial least squares, canonical correlation analysis and their nonlinear counterparts. Descriptive tools include scatter diagrams, Hotelling’s T2 statistics and contribution plots. The course has a strong emphasis on biomedical applications and presents associated results from studies related to autism, tissue engineering and stress-strain modeling.

? credits
Prereqs:
none

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998