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.
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References
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Brauner, M.W., Brauner, N., Hammer, P.L., Lozina, I., Valeyre, D. (2007). Logical Analysis of Computed Tomography Data to Differentiate Entities of Idiopathic Interstitial Pneumonias. In: Pardalos, P.M., Boginski, V.L., Vazacopoulos, A. (eds) Data Mining in Biomedicine. Springer Optimization and Its Applications, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-69319-4_12
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DOI: https://doi.org/10.1007/978-0-387-69319-4_12
Publisher Name: Springer, Boston, MA
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