Feature Selection Using Automatic Programming Methods in Hypertension Risk Prediction

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dc.contributor.authorYagmurcu, Merve
dc.contributor.authorArslan, Sibel
dc.date.accessioned2025-05-04T16:41:58Z
dc.date.available2025-05-04T16:41:58Z
dc.date.issued2024
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 -- 21 September 2024 through 22 September 2024 -- Malatya -- 203423
dc.description.abstractHypertension is a condition where the pressure in the blood vessels is higher than normal. It can lead to serious problems such as heart attack, stroke, heart failure, kidney disease and vision problems. Therefore, early diagnosis and treatment is important to find appropriate treatment strategies for the disease. In this study, automatic programming (AP) methods, were used and compared to analyze the risk of hypertension. These methods are Artificial Bee Colony Programming developed from the behavior of honeybees, Genetic Programming (GP) inspired by genetic selection and Immune Plasma Programming (IPP) based on immune plasma therapy. According to the performance evaluations obtained from the methods, GP and IPP were the most successful methods with test success rates of 0.91% and 0.89% respectively. In future research, Due to the success of the AP methods, we aim to develop different versions for health problems. © 2024 IEEE.
dc.identifier.doi10.1109/IDAP64064.2024.10711046
dc.identifier.isbn979-833153149-2
dc.identifier.scopus2-s2.0-85207883526
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/IDAP64064.2024.10711046
dc.identifier.urihttps://hdl.handle.net/20.500.12418/35017
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250504
dc.subjectArtificial Bee Colony Programming
dc.subjectAutomatic Programming
dc.subjectGenetic Programming
dc.subjectHypertension
dc.subjectImmune Plasma Programming
dc.titleFeature Selection Using Automatic Programming Methods in Hypertension Risk Prediction
dc.typeConference Object

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