JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 356
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #305990
Title: A Review of Classification Methods That Could Be Used to Identify a Subset of Patients in a Clinical Study
Author(s): Alexander Cambon*+ and Shesh N. Rai
Companies: University of Louisville and University of Louisville
Address: School of Pub Health and Information Sci, Louisville, KY, 40292, United States
Keywords: classification ; machine learning ; dimension reduction

It is now widely recognized that many treatments for cancer are effective for a subset of a population. However large clinical studies for cancer treatments are powered to detect an overall treatment effect. In this study, classification methods which could be used in a clinical study setting to identify subsets of patients which are more sensitive to treatment or more prone to relapse are reviewed. Some approaches to sample size planning for classifiers, quantification of uncertainty, and methods which assess added value of genomic/high dimensional data to clinical covariates are also highlighted. Classification methods such as logistic classification, Random Forests, and Boosting will be studied.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.