Birlik, Ayşe BanuTozan, HakanKöse, Kevser Banu2025-04-182025-04-182024Birlik, A. B., Tozan, H., & Köse, K. B. (2024). A Review on Machine Learning Applications: CVI Risk Assessment. Tehnički vjesnik, 31(4), 1422-1430.1330-36511848-6339http://dx.doi.org/10.17559/TV-20230326000480https://hdl.handle.net/20.500.12713/6410Comprehensive 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.eninfo:eu-repo/semantics/openAccessCardiovascularDecision-MakingMachine LearningPrediction ModelRisk AssessmentOther31414221430WOS:0012584352000442-s2.0-8519773149710.17559/TV-20230326000480