A Review on Machine Learning Applications: CVI Risk Assessment

Birlik A. B., TOZAN H., KÖSE K. B.

Tehnicki Vjesnik, cilt.31, sa.4, ss.1422-1430, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 31 Sayı: 4
  • Basım Tarihi: 2024
  • Doi Numarası: 10.17559/tv-20230326000480
  • Dergi Adı: Tehnicki Vjesnik
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1422-1430
  • Anahtar Kelimeler: cardiovascular, decision-making, machine learning, prediction model, risk assessment
  • İstanbul Medipol Üniversitesi Adresli: Evet

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.