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An automation of acute leukemia diagnostics using artificial neural networks


D. R. Khamatdinova, A. R. Ganeev, Z. R. Khamatdinova

B-lineage and T-lineage acute lymphoblastic leukemia diagnostics is possible with analysis of 14 indexes namely bone marrow markers CD (Clusters of Differentiation). It is proposed the automation the process of diagnostics using Artificial Neural Network . Developed software for data processing can help medical staff, even not specialized in immunology, to diagnose by oneself. Analyzes database, collected by the BD FACSCalibur multicolor flow cytometer, gave an opportunity to make reference samples, that are necessary for neural network training. MatLAB numerical computing environment with Neural Network Toolbox were used for building and training of the neural network. This software demonstrates rather effective and accurate work of the Neural Network.

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