Prediction of disorders with significant coronary lesions using machine learning in patients admitted with chest symptom.
Jae Young ChoiJae Hoon LeeYuri ChoiYunKyong HyonYong Hwan KimPublished in: PloS one (2022)
The assessment using the fittest importance variables can assist physicians in differentiating mimicking diseases in which coronary angiography may not be required in patients suspected of having acute coronary syndrome in emergency department.
Keyphrases
- emergency department
- acute coronary syndrome
- end stage renal disease
- ejection fraction
- newly diagnosed
- primary care
- coronary artery disease
- coronary artery
- peritoneal dialysis
- pulmonary embolism
- prognostic factors
- heart failure
- magnetic resonance
- aortic stenosis
- patient reported outcomes
- left ventricular
- contrast enhanced
- aortic valve
- adverse drug