The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers
Diabetes is a disease which, as well as prevention, requires a high level of care, such as monitoring the blood sugar changes. The timely diagnosis of disease plays an important role in its treatment and decreases the damage caused by the disease. Therefore, it is essential to diagnose diabetes. Sin...
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| Format: | Article |
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University of Qom
2022-03-01
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| Series: | مدیریت مهندسی و رایانش نرم |
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| Online Access: | https://jemsc.qom.ac.ir/article_1280_748eaa59f91950f90af6529e1c1c1b21.pdf |
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| _version_ | 1832577592831508480 |
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| author | Zeinab Hassani Najmeh Samadiani |
| author_facet | Zeinab Hassani Najmeh Samadiani |
| author_sort | Zeinab Hassani |
| collection | DOAJ |
| description | Diabetes is a disease which, as well as prevention, requires a high level of care, such as monitoring the blood sugar changes. The timely diagnosis of disease plays an important role in its treatment and decreases the damage caused by the disease. Therefore, it is essential to diagnose diabetes. Since hybrid algorithms have a high ability to predict and diagnose various diseases, this article presents an intelligent approach to the diagnosis of this disease, using a hybrid algorithm of flower pollination and K-nearest neighbor ensemble. The accuracy of the proposed method is measured to be 97.78, by using Pima Indians Diabetes (PID) dataset, consisting of 768 samples and 8 features. The results show that the accuracy of this approach has significantly increased compared with the previous studies, and confirms the superiority of the proposed method. |
| format | Article |
| id | doaj-art-e2977d00919443648f3075044315fb05 |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2022-03-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-e2977d00919443648f3075044315fb052025-01-30T20:18:14ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752022-03-0181374810.22091/jemsc.2019.12801280The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN ClassifiersZeinab Hassani0Najmeh Samadiani1computer science Kosar university of Bojnordcomputer Kosar university of BojnordDiabetes is a disease which, as well as prevention, requires a high level of care, such as monitoring the blood sugar changes. The timely diagnosis of disease plays an important role in its treatment and decreases the damage caused by the disease. Therefore, it is essential to diagnose diabetes. Since hybrid algorithms have a high ability to predict and diagnose various diseases, this article presents an intelligent approach to the diagnosis of this disease, using a hybrid algorithm of flower pollination and K-nearest neighbor ensemble. The accuracy of the proposed method is measured to be 97.78, by using Pima Indians Diabetes (PID) dataset, consisting of 768 samples and 8 features. The results show that the accuracy of this approach has significantly increased compared with the previous studies, and confirms the superiority of the proposed method.https://jemsc.qom.ac.ir/article_1280_748eaa59f91950f90af6529e1c1c1b21.pdfdiabetesensemble of a subset of k-nearest neighbor classifiersflower pollination algorithmk-nearest neighbor algorithm |
| spellingShingle | Zeinab Hassani Najmeh Samadiani The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers مدیریت مهندسی و رایانش نرم diabetes ensemble of a subset of k-nearest neighbor classifiers flower pollination algorithm k-nearest neighbor algorithm |
| title | The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers |
| title_full | The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers |
| title_fullStr | The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers |
| title_full_unstemmed | The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers |
| title_short | The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers |
| title_sort | diagnosis of diabetes using a hybrid algorithm consisting of the flower pollination algorithm and an ensemble of a subset of k nn classifiers |
| topic | diabetes ensemble of a subset of k-nearest neighbor classifiers flower pollination algorithm k-nearest neighbor algorithm |
| url | https://jemsc.qom.ac.ir/article_1280_748eaa59f91950f90af6529e1c1c1b21.pdf |
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