Alaa AM, Bolton T, Di Angelantonio E, et al. Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants. PLoS One 2019; 14: e0213653.
2.
AlkhouliMAlqahtaniFAlreshidanM, et al.Incidence, predictors, and outcomes of early acute myocardial infarction following coronary artery bypass grafting. Am J Cardiol2019; 124: 1027–1030.
3.
ShahMPatilSPatelB, et al.Causes and predictors of 30-day readmission in patients with acute myocardial infarction and cardiogenic shock. Circulation: Heart Failure2018; 11: e004310–e004310.
4.
Al’Aref SJ, Maliakal G, Singh G, et al. Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry. Eur Heart J. Epub ahed of print 12 September 2019. DOI: 10.1093/eurheartj/ehz565.
5.
PiepoliMFHoesAWAgewallS, et al.2016 European guidelines on cardiovascular disease prevention in clinical practice: the Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts). Developed with the special contribution of the European Association for Cardiovascular Prevention and Rehabilitation (EACPR). Eur Heart J2016; 37: 2315–2381.
6.
WengSFRepsJKaiJ, et al.Can machine-learning improve cardiovascular risk prediction using routine clinical data?PLoS One2017; 12: e0174944–e0174944.
7.
MedirattaNChalmersJPullanM, et al.In-hospital mortality and long-term survival after coronary artery bypass surgery in young patients. Eur J Cardio-Thorac Surg2012; 43: 1014–1021.
8.
GotoSKimuraMKatsumataY, et al.Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients. PLoS One2019; 14: e0210103–e0210103.
9.
HannunAYRajpurkarPHaghpanahiM, et al.Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nat Med2019; 25: 65–69.
10.
MotwaniMDeyDBermanDS, et al.Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis. Eur Heart J2017; 38: 500–507.
