Abstract:
:Prognosis of B-Chronic Lymphocytic Leukemia (B-CLL) remains a challenging problem in medical research and practice. While the parameters obtained by flow cytometry analysis form the basis of the diagnosis of the disease, the question whether these parameters offer additional prognostic information still remains open. In this work, we attempt to provide computer-assisted support to the clinical experts of the field, by deploying a classification system for B-CLL multiparametric prognosis that combines various heterogeneous (clinical, laboratory and flow cytometry) parameters associated with the disease. For this purpose, we employ the naïve-Bayes classifier and propose an algorithm that improves its performance. The algorithm discretizes the continuous classification attributes (candidate prognostic parameters) and selects the most useful subset of them to optimize the classification accuracy. Thus, in addition to the high classification accuracy achieved, the proposed approach also suggests the most informative parameters for the prognosis. The experimental results demonstrate that the inclusion of flow cytometry parameters in our system improves prognosis.
journal_name
Comput Methods Programs Biomedjournal_title
Computer methods and programs in biomedicineauthors
Lakoumentas J,Drakos J,Karakantza M,Sakellaropoulos G,Megalooikonomou V,Nikiforidis Gdoi
10.1016/j.cmpb.2012.02.009subject
Has Abstractpub_date
2012-10-01 00:00:00pages
158-67issue
1eissn
0169-2607issn
1872-7565pii
S0169-2607(12)00061-2journal_volume
108pub_type
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