Computational intelligence in the identification of Covid-19 patients by using KNN-SVM Classifier
Initiatives to mitigate the persistent coronavirus disease 2019 (COVID-19) crisis shown that quick, sensitive, and extensive screening is essential for managing the present epidemic and future pandemics. This virus seeks to infect the lungs by generating white, patchy opacities inside them. This re...
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| Format: | Article |
| Language: | English |
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College of Computer and Information Technology – University of Wasit, Iraq
2024-12-01
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| Series: | Wasit Journal of Computer and Mathematics Science |
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| Online Access: | http://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/306 |
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| author | shaymaa adnan |
| author_facet | shaymaa adnan |
| author_sort | shaymaa adnan |
| collection | DOAJ |
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Initiatives to mitigate the persistent coronavirus disease 2019 (COVID-19) crisis shown that quick, sensitive, and extensive screening is essential for managing the present epidemic and future pandemics. This virus seeks to infect the lungs by generating white, patchy opacities inside them. This research presents an advanced methodology employing deep learning techniques for the analysis of medical pictures pertaining to respiratory disorders. This experiment included two data sets, the initial one including normal lungs sourced from the Kaggle data pool. We acquired the anomalous lungs from https://github.com/muhammedtalo/COVID-19. We applied Principal Component Analysis (PCA) and Histogram of Gradients (HOG) as extract features. while we conducted a classification process using K nearest neighbors (KNN) and Support Vector Machine (SVM) algorithms . Results showed that the classification accuracy with SVM for Covid-19 identification is 88.54% while with KNN is 82.31%
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| format | Article |
| id | doaj-art-a80aa642cbeb48bb9235d4ad832c6a59 |
| institution | Kabale University |
| issn | 2788-5879 2788-5887 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | College of Computer and Information Technology – University of Wasit, Iraq |
| record_format | Article |
| series | Wasit Journal of Computer and Mathematics Science |
| spelling | doaj-art-a80aa642cbeb48bb9235d4ad832c6a592025-01-30T05:23:42ZengCollege of Computer and Information Technology – University of Wasit, IraqWasit Journal of Computer and Mathematics Science2788-58792788-58872024-12-013410.31185/wjcms.306Computational intelligence in the identification of Covid-19 patients by using KNN-SVM Classifiershaymaa adnan0University of Information Technology & Communications, College of Business Informatics Technology, Business Information Initiatives to mitigate the persistent coronavirus disease 2019 (COVID-19) crisis shown that quick, sensitive, and extensive screening is essential for managing the present epidemic and future pandemics. This virus seeks to infect the lungs by generating white, patchy opacities inside them. This research presents an advanced methodology employing deep learning techniques for the analysis of medical pictures pertaining to respiratory disorders. This experiment included two data sets, the initial one including normal lungs sourced from the Kaggle data pool. We acquired the anomalous lungs from https://github.com/muhammedtalo/COVID-19. We applied Principal Component Analysis (PCA) and Histogram of Gradients (HOG) as extract features. while we conducted a classification process using K nearest neighbors (KNN) and Support Vector Machine (SVM) algorithms . Results showed that the classification accuracy with SVM for Covid-19 identification is 88.54% while with KNN is 82.31% http://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/306Covid-19, Chest X-rays, AI, Neural classifiers |
| spellingShingle | shaymaa adnan Computational intelligence in the identification of Covid-19 patients by using KNN-SVM Classifier Wasit Journal of Computer and Mathematics Science Covid-19, Chest X-rays, AI, Neural classifiers |
| title | Computational intelligence in the identification of Covid-19 patients by using KNN-SVM Classifier |
| title_full | Computational intelligence in the identification of Covid-19 patients by using KNN-SVM Classifier |
| title_fullStr | Computational intelligence in the identification of Covid-19 patients by using KNN-SVM Classifier |
| title_full_unstemmed | Computational intelligence in the identification of Covid-19 patients by using KNN-SVM Classifier |
| title_short | Computational intelligence in the identification of Covid-19 patients by using KNN-SVM Classifier |
| title_sort | computational intelligence in the identification of covid 19 patients by using knn svm classifier |
| topic | Covid-19, Chest X-rays, AI, Neural classifiers |
| url | http://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/306 |
| work_keys_str_mv | AT shaymaaadnan computationalintelligenceintheidentificationofcovid19patientsbyusingknnsvmclassifier |