Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLP
Blood donation has an important and critical role to preserve the health and survival of human life. In today's world, despite the enormous scientific advancements and the great developments in medical sciences, adequate supply of healthy blood is one of the challenges and concerns of the medic...
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University of Qom
2020-03-01
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| Series: | مدیریت مهندسی و رایانش نرم |
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| Online Access: | https://jemsc.qom.ac.ir/article_1278_e4e4008ddabfb105a7bf773616a03ae4.pdf |
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| author | Arash Fahmihassan Mohammadreza Moghari Omidmahdi Ebadati |
| author_facet | Arash Fahmihassan Mohammadreza Moghari Omidmahdi Ebadati |
| author_sort | Arash Fahmihassan |
| collection | DOAJ |
| description | Blood donation has an important and critical role to preserve the health and survival of human life. In today's world, despite the enormous scientific advancements and the great developments in medical sciences, adequate supply of healthy blood is one of the challenges and concerns of the medical community in the world. Preserving and supplying the volume of blood required in blood banks of each region, and the diverse blood groups with the connections between them, with assuming that the number of blood groups are rarer; makes the prediction and planning of blood donation more and more complicated and important during the time. The use of data mining in hospitals and blood transfer centers databases helps in the discovery of relations, so that they can have a future prediction based on the past information. Accordingly, they have better diagnosed and successful cure various illnesses and show the patterns of new injuries. In this paper, we try to use data mining and machine learning techniques in decision making levels at mentioned field, to use this mechanism for prediction that how much blood will be donate to blood transfusion centers and blood banks in different period time, to estimate and supply the required blood volume of blood banks in different areas. In this regard, we use several classification algorithms in supervised learning for the prediction, including decision tree algorithms, KNN, SVM and MLP, these algorithms are implemented to predict and results of accuracy are presented. |
| format | Article |
| id | doaj-art-9d5be7125f024b2f9f0b370caf3376a4 |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2020-03-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-9d5be7125f024b2f9f0b370caf3376a42025-01-30T20:17:17ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752020-03-016110912910.22091/jemsc.2018.12781278Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLPArash Fahmihassan0Mohammadreza Moghari1Omidmahdi Ebadati2Faculty of Mathematical Sciences and Computer, Kharazmi University, Tehran, IranFaculty of Mathematical Sciences and Computer, Kharazmi University, Tehran, IranInformation Technology Management department ,Kharazmi University, Tehran, IranBlood donation has an important and critical role to preserve the health and survival of human life. In today's world, despite the enormous scientific advancements and the great developments in medical sciences, adequate supply of healthy blood is one of the challenges and concerns of the medical community in the world. Preserving and supplying the volume of blood required in blood banks of each region, and the diverse blood groups with the connections between them, with assuming that the number of blood groups are rarer; makes the prediction and planning of blood donation more and more complicated and important during the time. The use of data mining in hospitals and blood transfer centers databases helps in the discovery of relations, so that they can have a future prediction based on the past information. Accordingly, they have better diagnosed and successful cure various illnesses and show the patterns of new injuries. In this paper, we try to use data mining and machine learning techniques in decision making levels at mentioned field, to use this mechanism for prediction that how much blood will be donate to blood transfusion centers and blood banks in different period time, to estimate and supply the required blood volume of blood banks in different areas. In this regard, we use several classification algorithms in supervised learning for the prediction, including decision tree algorithms, KNN, SVM and MLP, these algorithms are implemented to predict and results of accuracy are presented.https://jemsc.qom.ac.ir/article_1278_e4e4008ddabfb105a7bf773616a03ae4.pdfdata miningmachine learningdecision tree algorithms |
| spellingShingle | Arash Fahmihassan Mohammadreza Moghari Omidmahdi Ebadati Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLP مدیریت مهندسی و رایانش نرم data mining machine learning decision tree algorithms |
| title | Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLP |
| title_full | Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLP |
| title_fullStr | Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLP |
| title_full_unstemmed | Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLP |
| title_short | Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLP |
| title_sort | prediction of blood donations using data mining based on the decision tree algorithms knn svm and mlp |
| topic | data mining machine learning decision tree algorithms |
| url | https://jemsc.qom.ac.ir/article_1278_e4e4008ddabfb105a7bf773616a03ae4.pdf |
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