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An Approach for Leukemia Classification Based on Cooperative Game Theory
Hematological malignancies are the types of cancer that affect blood, bone marrow and lymph nodes. As these tissues are naturally connected through the immune system, a disease affecting one of them will often affect the others as well. The hematological malignancies include; Leukemia, Lymphoma, Mul...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOS Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605502/ https://www.ncbi.nlm.nih.gov/pubmed/21988887 http://dx.doi.org/10.3233/ACP-2011-0016 |
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author | Torkaman, Atefeh Charkari, Nasrollah Moghaddam Aghaeipour, Mahnaz |
author_facet | Torkaman, Atefeh Charkari, Nasrollah Moghaddam Aghaeipour, Mahnaz |
author_sort | Torkaman, Atefeh |
collection | PubMed |
description | Hematological malignancies are the types of cancer that affect blood, bone marrow and lymph nodes. As these tissues are naturally connected through the immune system, a disease affecting one of them will often affect the others as well. The hematological malignancies include; Leukemia, Lymphoma, Multiple myeloma. Among them, leukemia is a serious malignancy that starts in blood tissues especially the bone marrow, where the blood is made. Researches show, leukemia is one of the common cancers in the world. So, the emphasis on diagnostic techniques and best treatments would be able to provide better prognosis and survival for patients. In this paper, an automatic diagnosis recommender system for classifying leukemia based on cooperative game is presented. Through out this research, we analyze the flow cytometry data toward the classification of leukemia into eight classes. We work on real data set from different types of leukemia that have been collected at Iran Blood Transfusion Organization (IBTO). Generally, the data set contains 400 samples taken from human leukemic bone marrow. This study deals with cooperative game used for classification according to different weights assigned to the markers. The proposed method is versatile as there are no constraints to what the input or output represent. This means that it can be used to classify a population according to their contributions. In other words, it applies equally to other groups of data. The experimental results show the accuracy rate of 93.12%, for classification and compared to decision tree (C4.5) with (90.16%) in accuracy. The result demonstrates that cooperative game is very promising to be used directly for classification of leukemia as a part of Active Medical decision support system for interpretation of flow cytometry readout. This system could assist clinical hematologists to properly recognize different kinds of leukemia by preparing suggestions and this could improve the treatment of leukemic patients. |
format | Online Article Text |
id | pubmed-4605502 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | IOS Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-46055022015-12-13 An Approach for Leukemia Classification Based on Cooperative Game Theory Torkaman, Atefeh Charkari, Nasrollah Moghaddam Aghaeipour, Mahnaz Anal Cell Pathol (Amst) Other Hematological malignancies are the types of cancer that affect blood, bone marrow and lymph nodes. As these tissues are naturally connected through the immune system, a disease affecting one of them will often affect the others as well. The hematological malignancies include; Leukemia, Lymphoma, Multiple myeloma. Among them, leukemia is a serious malignancy that starts in blood tissues especially the bone marrow, where the blood is made. Researches show, leukemia is one of the common cancers in the world. So, the emphasis on diagnostic techniques and best treatments would be able to provide better prognosis and survival for patients. In this paper, an automatic diagnosis recommender system for classifying leukemia based on cooperative game is presented. Through out this research, we analyze the flow cytometry data toward the classification of leukemia into eight classes. We work on real data set from different types of leukemia that have been collected at Iran Blood Transfusion Organization (IBTO). Generally, the data set contains 400 samples taken from human leukemic bone marrow. This study deals with cooperative game used for classification according to different weights assigned to the markers. The proposed method is versatile as there are no constraints to what the input or output represent. This means that it can be used to classify a population according to their contributions. In other words, it applies equally to other groups of data. The experimental results show the accuracy rate of 93.12%, for classification and compared to decision tree (C4.5) with (90.16%) in accuracy. The result demonstrates that cooperative game is very promising to be used directly for classification of leukemia as a part of Active Medical decision support system for interpretation of flow cytometry readout. This system could assist clinical hematologists to properly recognize different kinds of leukemia by preparing suggestions and this could improve the treatment of leukemic patients. IOS Press 2011 2011-10-11 /pmc/articles/PMC4605502/ /pubmed/21988887 http://dx.doi.org/10.3233/ACP-2011-0016 Text en Copyright © 2011 Hindawi Publishing Corporation and the authors. |
spellingShingle | Other Torkaman, Atefeh Charkari, Nasrollah Moghaddam Aghaeipour, Mahnaz An Approach for Leukemia Classification Based on Cooperative Game Theory |
title | An Approach for Leukemia Classification Based on Cooperative Game Theory |
title_full | An Approach for Leukemia Classification Based on Cooperative Game Theory |
title_fullStr | An Approach for Leukemia Classification Based on Cooperative Game Theory |
title_full_unstemmed | An Approach for Leukemia Classification Based on Cooperative Game Theory |
title_short | An Approach for Leukemia Classification Based on Cooperative Game Theory |
title_sort | approach for leukemia classification based on cooperative game theory |
topic | Other |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605502/ https://www.ncbi.nlm.nih.gov/pubmed/21988887 http://dx.doi.org/10.3233/ACP-2011-0016 |
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