Risk factors associated with major adverse cardiac and cerebrovascular events following percutaneous coronary intervention: a 10-year follow-up comparing random survival forest and Cox proportional-hazards model.
Maryam FarhadianSahar Dehdar KarsidaniAzadeh MozayanimonfaredHossein MahjubPublished in: BMC cardiovascular disorders (2021)
Machine-learning prediction models such as RSF showed better performance than the Cox proportional hazards model for the prediction of MACCE during long-term follow-up after PCI.
Keyphrases
- percutaneous coronary intervention
- machine learning
- acute coronary syndrome
- acute myocardial infarction
- coronary artery disease
- st segment elevation myocardial infarction
- antiplatelet therapy
- coronary artery bypass grafting
- left ventricular
- climate change
- atrial fibrillation
- emergency department
- artificial intelligence
- heart failure
- coronary artery bypass
- neural network