A System Architecture Based on the RNN Classifier for Heart Disease Detection

dc.contributor.authorGöreke, Volkan
dc.date.accessioned2024-01-10T06:36:50Z
dc.date.available2024-01-10T06:36:50Z
dc.date.issuedAğustos 2023tr
dc.departmentSivas Meslek Yüksekokulutr
dc.description.abstractAbstract— Diagnosing heart disease is a challenging process for physicians. Insufficient number of experts, late diagnosis and misdiagnosis are the difficulties in this process. To overcome these difficulties, systems based on artificial intelligence are used today. Appropriate system selection and obtaining sufficient data sets are a challenge for researchers. In this study, a high-performance CAD architecture was proposed for the detection of heart disease. The proposed architecture has shown a higher performance than the studies carried out using the UCI dataset in the literature.tr
dc.identifier.urihttps://hdl.handle.net/20.500.12418/14250
dc.language.isoenen_US
dc.relation.publicationcategoryUluslararası Konferans Öğesitr
dc.rightsinfo:eu-repo/semantics/openAccesstr
dc.titleA System Architecture Based on the RNN Classifier for Heart Disease Detectionen_US
dc.typePresentationen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Yükleniyor...
Küçük Resim
İsim:
ICAT23 BİLDİRİ VE KANIT.pdf
Boyut:
2.54 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama: