A review on machine learning applications: CVI risk assessment

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dc.authorscopusidAyşe Banu Birlik / 59207955600
dc.authorwosidAyşe Banu Birlik / KWA-0602-2024
dc.contributor.authorBirlik, Ayşe Banu
dc.contributor.authorTozan, Hakan
dc.contributor.authorKöse, Kevser Banu
dc.date.accessioned2025-04-18T07:03:07Z
dc.date.available2025-04-18T07:03:07Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Sağlık Hizmetleri Meslek Yüksekokulu, Tıbbi Görüntüleme Teknikleri Programı
dc.description.abstractComprehensive literature has been published on the development of digital health applications using machine learning methods in cardiovascular surgery. Many machine learning methods have been applied in clinical decision-making processes, particularly for risk estimation models. This review of the literature shares an update on machine learning applications for cardiovascular intervention (CVI) risk assessment. This study selected peer-reviewed scientific publications providing sufficient detail about machine learning methods and outcomes predicting short-term CVI risk in cardiac surgery. Thirteen articles fulfilling pre-set criteria were reviewed and tables were created presenting the relevant characteristics of the studies. The review demonstrates the usefulness of machine learning methods in high-risk CVI applications, identifies the need for improvement, and provides efficient support for future prediction models for the healthcare system.
dc.identifier.citationBirlik, A. B., Tozan, H., & Köse, K. B. (2024). A Review on Machine Learning Applications: CVI Risk Assessment. Tehnički vjesnik, 31(4), 1422-1430.
dc.identifier.doi10.17559/TV-20230326000480
dc.identifier.endpage1430
dc.identifier.issn1330-3651
dc.identifier.issn1848-6339
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85197731497
dc.identifier.startpage1422
dc.identifier.urihttp://dx.doi.org/10.17559/TV-20230326000480
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6410
dc.identifier.volume31
dc.identifier.wosWOS:001258435200044
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorBirlik, Ayşe Banu
dc.institutionauthoridAyşe Banu Birlik / 0000-0001-5148-3784
dc.language.isoen
dc.publisherStrojarski facultet
dc.relation.ispartofTehnicki vjesnik
dc.relation.publicationcategoryDiğer
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectCardiovascular
dc.subjectDecision-Making
dc.subjectMachine Learning
dc.subjectPrediction Model
dc.subjectRisk Assessment
dc.titleA review on machine learning applications: CVI risk assessment
dc.typeOther

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