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

International Standard Serial Number (ISSN)

  • 1615-9853

Digital Object Identifier (DOI)

  • 10.1002/pmic.200300521

Language

  • eng

Conference Location

  • Germany