A review on machine learning applications: CVI risk assessment
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Strojarski facultet
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Comprehensive 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.
Açıklama
Anahtar Kelimeler
Cardiovascular, Decision-Making, Machine Learning, Prediction Model, Risk Assessment
Kaynak
Tehnicki vjesnik
WoS Q Değeri
Scopus Q Değeri
Cilt
31
Sayı
4
Künye
Birlik, A. B., Tozan, H., & Köse, K. B. (2024). A Review on Machine Learning Applications: CVI Risk Assessment. Tehnički vjesnik, 31(4), 1422-1430.
