Machine learning-based risk profile classification of patients undergoing elective heart valve surgery.
Ulrich BodenhoferBettina Haslinger-EistererAlexander MinichmayerGeorg HermanutzJens MeierPublished in: European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery (2022)
Advanced machine learning methods can predict outcomes of valve surgery procedures with higher accuracy than established risk scores based on logistic regression on pre-selected parameters. This approach is generalizable to other elective high-risk interventions and allows for training models to the cohorts of specific institutions.
Keyphrases
- machine learning
- patients undergoing
- minimally invasive
- aortic valve
- coronary artery bypass
- mitral valve
- artificial intelligence
- deep learning
- big data
- aortic stenosis
- surgical site infection
- heart failure
- physical activity
- type diabetes
- acute coronary syndrome
- transcatheter aortic valve replacement
- adipose tissue
- weight loss
- ejection fraction