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2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2015)
Washington, DC, USA
Nov. 9, 2015 to Nov. 12, 2015
ISBN: 978-1-4673-6798-1
pp: 742-745
Evdoxia Papadopoulou , Informatics and Telematics Institute, Centre of Research and Technology, Thessaloniki, Greece, 57001
Konstantia Kotta , Institute of Applied Bioscience, Centre of Research and Technology, Thessaloniki, Greece, 57001
Panagiotis Moschonas , Informatics and Telematics Institute, Centre of Research and Technology, Thessaloniki, Greece, 57001
Vassiliki Douka , Hematology Department and HCT Unit, G. Papanicolaou Hospital, Thessaloniki, Greece, 57010
Achilles Anagnostopoulos , Hematology Department and HCT Unit, G. Papanicolaou Hospital, Thessaloniki, Greece, 57010
Kostas Stamatopoulos , Institute of Applied Bioscience, Centre of Research and Technology, Thessaloniki, Greece, 57001
Dimitrios Tzovaras , Informatics and Telematics Institute, Centre of Research and Technology, Thessaloniki, Greece, 57001
ABSTRACT
Flow cytometry (FC) is widely used for diagnostic purposes in clinical practice. This analysis typically aims at clustering cellular events according to their biological characteristics, known as gating, and then use the selected clusters in order to conclude about clinical outcomes. As each step of this process is highly subjective, various proposed methods have attempted to automate each step of the procedure separately, but any method has been proposed in order to automate the whole diagnostic process. We constructed a tool that simulates the experts decisions during the whole process in order to conclude if a sample is pathologic or not ('healthy'). We used flow cytometric data from 10 individuals with a diagnosis of chronic lymphocytic leukemia (CLL) from a panel that produces 7 files for each sample. With the help of the present tool we were able to identify whether the analysis of the tested sample confirms the diagnosis of CLL, thus successfully reproducing the experts' decisions at each step of the diagnostic workflow. The validation was conducted by experts against the traditional manual procedure. The proposed methodology is the first attempt to automate the entire process, which is a prerequisite for a fully automated diagnostic system that would ensure objectivity to the clinical diagnostic procedure. The experimental results presented herein show that our proposed new technique has satisfying performance at each level of evaluation.
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CITATION

E. Papadopoulou et al., "Chronic lymphocytic leukemia patient classification methodology through flow cytometry analysis," 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, DC, USA, 2015, pp. 742-745.
doi:10.1109/BIBM.2015.7359778
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