Logical Analysis of Computed Tomography Data to Differentiate Entities of Idiopathic Interstitial Pneumonias

M. W. Brauner (), N. Brauner (), P. L. Hammer (), I. Lozina () and D. Valeyre
Additional contact information
M. W. Brauner: Université Paris 13 et Hôpital Avicenne AP-HP
N. Brauner: Laboratoire Leibniz-IMAG
P. L. Hammer: Rutgers University
I. Lozina: Rutgers University
D. Valeyre: Université Paris 13 et Hôpital Avicenne AP-HP

A chapter in Data Mining in Biomedicine, 2007, pp 193-208 from Springer

Abstract: Abstract The aim of this chapter is to analyze computed tomography (CT) data by using the Logical Analysis of Data (LAD) methodology in order to distinguish between three types of idiopathic interstitial pneumonias (IIPs). The chapter demonstrates that LAD can distinguish different forms of IIPs with high accuracy It shows also that the patterns developed by LAD techniques provide additional information about outliers, redundant features, the relative significance of attributes, and makes possible the identification of promoters and blockers of various forms of IIPs.

Keywords: Idiopathic Pulmonary Fibrosis; Logical Analysis; Idiopathic Pulmonary Fibrosis Patient; Polygonal Line; Negative Pattern (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (7)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-69319-4_12

Ordering information: This item can be ordered from
http://www.springer.com/9780387693194

DOI: 10.1007/978-0-387-69319-4_12

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().