DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSIS
Electrocardiogram (ECG) data are usually used to diagnose cardiovascular disease (CVD) with the help of a revolutionary algorithm. Feature selection is a crucial step in the development of accurate and reliable diagnostic models for CVDs. This research introduces the dynamic threshold genetic algori...
| Main Authors: | , , |
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| Format: | Article |
| Language: | Arabic |
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University of Information Technology and Communications
2023-12-01
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| Series: | Iraqi Journal for Computers and Informatics |
| Subjects: | |
| Online Access: | https://ijci.uoitc.edu.iq/index.php/ijci/article/view/456 |
| _version_ | 1797371515254079488 |
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| author | Hasanain F. Hashim Meriam JEMEL Nadia Ben Azzouna |
| author_facet | Hasanain F. Hashim Meriam JEMEL Nadia Ben Azzouna |
| author_sort | Hasanain F. Hashim |
| collection | DOAJ |
| description | Electrocardiogram (ECG) data are usually used to diagnose cardiovascular disease (CVD) with the help of a revolutionary algorithm. Feature selection is a crucial step in the development of accurate and reliable diagnostic models for CVDs. This research introduces the dynamic threshold genetic algorithm (DTGA) algorithm, a type of genetic algorithm that is used for optimization problems and discusses its use in the context of feature selection. This research reveals the success of DTGA in selecting relevant ECG features that ultimately enhance accuracy and efficiency in the diagnosis of CVD. This work also proves the benefits of employing DTGA in clinical practice, including a reduction in the amount of time spent diagnosing patients and an increase in the precision with which individuals who are at risk of CVD can be identified. |
| first_indexed | 2024-03-08T18:21:09Z |
| format | Article |
| id | doaj.art-bc105985e4a84c0c8efbb9a66d7de72d |
| institution | Directory Open Access Journal |
| issn | 2313-190X 2520-4912 |
| language | Arabic |
| last_indexed | 2024-03-08T18:21:09Z |
| publishDate | 2023-12-01 |
| publisher | University of Information Technology and Communications |
| record_format | Article |
| series | Iraqi Journal for Computers and Informatics |
| spelling | doaj.art-bc105985e4a84c0c8efbb9a66d7de72d2023-12-30T22:09:17ZaraUniversity of Information Technology and CommunicationsIraqi Journal for Computers and Informatics2313-190X2520-49122023-12-014927382419DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSISHasanain F. Hashim0Meriam JEMEL1Nadia Ben Azzouna2Université de TunisUniversité de TunisUniversité de TunisElectrocardiogram (ECG) data are usually used to diagnose cardiovascular disease (CVD) with the help of a revolutionary algorithm. Feature selection is a crucial step in the development of accurate and reliable diagnostic models for CVDs. This research introduces the dynamic threshold genetic algorithm (DTGA) algorithm, a type of genetic algorithm that is used for optimization problems and discusses its use in the context of feature selection. This research reveals the success of DTGA in selecting relevant ECG features that ultimately enhance accuracy and efficiency in the diagnosis of CVD. This work also proves the benefits of employing DTGA in clinical practice, including a reduction in the amount of time spent diagnosing patients and an increase in the precision with which individuals who are at risk of CVD can be identified.https://ijci.uoitc.edu.iq/index.php/ijci/article/view/456ecggenetic algorithmfeature selectiondynamic thresholding |
| spellingShingle | Hasanain F. Hashim Meriam JEMEL Nadia Ben Azzouna DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSIS Iraqi Journal for Computers and Informatics ecg genetic algorithm feature selection dynamic thresholding |
| title | DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSIS |
| title_full | DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSIS |
| title_fullStr | DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSIS |
| title_full_unstemmed | DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSIS |
| title_short | DYNAMIC THRESHOLDING GA-BASED ECG FEATURE SELECTION IN CARDIOVASCULAR DISEASE DIAGNOSIS |
| title_sort | dynamic thresholding ga based ecg feature selection in cardiovascular disease diagnosis |
| topic | ecg genetic algorithm feature selection dynamic thresholding |
| url | https://ijci.uoitc.edu.iq/index.php/ijci/article/view/456 |
| work_keys_str_mv | AT hasanainfhashim dynamicthresholdinggabasedecgfeatureselectionincardiovasculardiseasediagnosis AT meriamjemel dynamicthresholdinggabasedecgfeatureselectionincardiovasculardiseasediagnosis AT nadiabenazzouna dynamicthresholdinggabasedecgfeatureselectionincardiovasculardiseasediagnosis |