Predicting stroke and mortality in mitral stenosis with atrial flutter: A machine learning approach.
Amer RaufAsif UllahUsha RathiZainab AshrafHidayat UllahAmna AshrafJateesh KumarMaria FarazWaheed AkhtarJahanzeb MalikJahanzeb MalikPublished in: Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc (2023)
The GBM model assimilates clinical data from all diagnostic modalities and significantly improves risk prediction performance and identification of key variables for the outcome of MS with AFL.
Keyphrases
- atrial fibrillation
- left atrial
- machine learning
- catheter ablation
- big data
- mitral valve
- mass spectrometry
- multiple sclerosis
- cardiovascular events
- left ventricular
- ms ms
- electronic health record
- artificial intelligence
- heart failure
- risk factors
- cardiovascular disease
- bioinformatics analysis
- deep learning
- aortic stenosis
- type diabetes
- aortic valve