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Article Dans Une Revue IEEE Journal of Biomedical and Health Informatics Année : 2015

A novel classification method for prediction of rectal bleeding in prostate cancer radiotherapy based on a semi-nonnegative ICA of 3D planned dose distributions

Résumé

The understanding of dose/side-effects relationships in prostate cancer radiotherapy is crucial to define appropriate individual's constraints for the therapy planning. Most of the existing methods to predict side effects do not fully exploit the rich spatial information conveyed by the three-dimensional planned dose distributions. We propose a new classification method for three-dimensional individuals' doses, based on a new semi-nonnegative ICA algorithm to identify patients at risk of presenting rectal bleeding from a population treated for prostate cancer. The method first determines two bases of vectors from the population data: the two bases span vector subspaces, which characterize patients with and without rectal bleeding, respectively. The classification is then achieved by calculating the distance of a given patient to the two subspaces. The results, obtained on a cohort of 87 patients (at two years follow-up) treated with radiotherapy, showed high performance in terms of sensitivity and specificity.
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Dates et versions

hal-01011843 , version 1 (24-06-2014)

Identifiants

Citer

Julie Coloigner, Aureline Fargeas, Amar Kachenoura, Lu Wang, Gael Dréan, et al.. A novel classification method for prediction of rectal bleeding in prostate cancer radiotherapy based on a semi-nonnegative ICA of 3D planned dose distributions. IEEE Journal of Biomedical and Health Informatics, 2015, 9 (3), pp.1168-1177. ⟨10.1109/JBHI.2014.2328315⟩. ⟨hal-01011843⟩
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