Decision tree classification of proteins identified by mass spectrometry of blood serum samples from people with and without lung cancer.
Journal Article (Journal Article)
A classification and regression tree (CART) model was trained to classify 41 clinical specimens as disease/nondisease based on 26 variables computed from the mass-to-charge ratio (m/z) and peak heights of proteins identified by mass spectroscopy. The CART model built on all of the specimens (no cross-validation) had an error rate of 4/41 = 10%. The CART model suggests that mass spectra peaks in the 8000-10,000, 20,000-30,000, 45,000-60, 000, and >125,000 m/z ranges may be valuable in distinguishing between the disease/nondisease specimens. The area under the receiver operating characteristics curve was 0.80 +/- 0.07 for leave-one-out cross-validation.
Full Text
Duke Authors
Cited Authors
- Markey, MK; Tourassi, GD; Floyd, CE
Published Date
- September 2003
Published In
Volume / Issue
- 3 / 9
Start / End Page
- 1678 - 1679
PubMed ID
- 12973724
Pubmed Central ID
- 12973724
International Standard Serial Number (ISSN)
- 1615-9853
Digital Object Identifier (DOI)
- 10.1002/pmic.200300521
Language
- eng
Conference Location
- Germany