Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm
Diabetes is one of the most common, dangerous and costly diseases in the world today, which is increasing at an alarming rate. The use of data mining methods can help in the early diagnosis of diabetes, which prevents the progression of this disease and many of its complications such as cardiovascul...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | fas |
| Published: |
University of Qom
2023-09-01
|
| Series: | مدیریت مهندسی و رایانش نرم |
| Subjects: | |
| Online Access: | https://jemsc.qom.ac.ir/article_2020_19d2033b69a54d884e36d62d1c4e5edf.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832577550054850560 |
|---|---|
| author | Reza Molaee Fard |
| author_facet | Reza Molaee Fard |
| author_sort | Reza Molaee Fard |
| collection | DOAJ |
| description | Diabetes is one of the most common, dangerous and costly diseases in the world today, which is increasing at an alarming rate. The use of data mining methods can help in the early diagnosis of diabetes, which prevents the progression of this disease and many of its complications such as cardiovascular disease, vision problems and kidney disease. Providing care and health services to people with diabetes provides useful information that can be used to identify, treat, follow-up care and even prevent diabetes. In this study, a new method is presented to improve the diagnosis and prevention of diabetes using data mining methods. In this research, the DBSCAN clustering algorithm is used to cluster the data. Then, using SVM, we classify the data to identify useful data, and finally, with the firefly algorithm, we increase the obtained data to increase we optimize performance with this algorithm. The results of this study indicate that the DBSCAN algorithm is more efficient than other clustering algorithms. Also, the SVM algorithm can achieve 98% accuracy, which compared to other data mining algorithms could achieve a higher accuracy percentage. |
| format | Article |
| id | doaj-art-ab0d0fbdc7a34a01a3b544134d0d0b17 |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2023-09-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-ab0d0fbdc7a34a01a3b544134d0d0b172025-01-30T20:18:53ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752023-09-0191364810.22091/JEMSC.2022.6575.11472020Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithmReza Molaee Fard0MSC. Department of industrial engineering, Azad university of dezfull. Email: rezamolae4@gmail.comDiabetes is one of the most common, dangerous and costly diseases in the world today, which is increasing at an alarming rate. The use of data mining methods can help in the early diagnosis of diabetes, which prevents the progression of this disease and many of its complications such as cardiovascular disease, vision problems and kidney disease. Providing care and health services to people with diabetes provides useful information that can be used to identify, treat, follow-up care and even prevent diabetes. In this study, a new method is presented to improve the diagnosis and prevention of diabetes using data mining methods. In this research, the DBSCAN clustering algorithm is used to cluster the data. Then, using SVM, we classify the data to identify useful data, and finally, with the firefly algorithm, we increase the obtained data to increase we optimize performance with this algorithm. The results of this study indicate that the DBSCAN algorithm is more efficient than other clustering algorithms. Also, the SVM algorithm can achieve 98% accuracy, which compared to other data mining algorithms could achieve a higher accuracy percentage.https://jemsc.qom.ac.ir/article_2020_19d2033b69a54d884e36d62d1c4e5edf.pdfdiabetes diagnosisdata miningdbscan algorithmsvm algorithmfirefly algorithm |
| spellingShingle | Reza Molaee Fard Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm مدیریت مهندسی و رایانش نرم diabetes diagnosis data mining dbscan algorithm svm algorithm firefly algorithm |
| title | Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm |
| title_full | Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm |
| title_fullStr | Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm |
| title_full_unstemmed | Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm |
| title_short | Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm |
| title_sort | provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm |
| topic | diabetes diagnosis data mining dbscan algorithm svm algorithm firefly algorithm |
| url | https://jemsc.qom.ac.ir/article_2020_19d2033b69a54d884e36d62d1c4e5edf.pdf |
| work_keys_str_mv | AT rezamolaeefard provideamethodtodiagnoseandoptimizediabetesusingdataminingmethodsandfireflyalgorithm |