Related references
Note: Only part of the references are listed.Using a machine learning approach to predict outcome after surgery for degenerative cervical myelopathy
Zamir G. Merali et al.
PLOS ONE (2019)
Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease
Andrew J. Steele et al.
PLOS ONE (2018)
Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records
Fatemeh Rahimian et al.
PLOS MEDICINE (2018)
Screening for atrial fibrillation: a European Heart Rhythm Association (EHRA) consensus document endorsed by the Heart Rhythm Society (HRS), Asia Pacific Heart Rhythm Society (APHRS), and Sociedad Latinoamericana de Estimulacin Cardiaca y Electrofisiologia (SOLAECE)
Georges H. Mairesse et al.
EUROPACE (2017)
Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016
Theo Vos et al.
LANCET (2017)
Can machine-learning improve cardiovascular risk prediction using routine clinical data?
Stephen F. Weng et al.
PLOS ONE (2017)
Accuracy of methods for detecting an irregular pulse and suspected atrial fibrillation: A systematic review and meta-analysis
Jaspal S. Taggar et al.
EUROPEAN JOURNAL OF PREVENTIVE CARDIOLOGY (2016)
2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS
Paulus Kirchhof et al.
EUROPEAN HEART JOURNAL (2016)
Machine Learning in Medicine
Rahul C. Deo
CIRCULATION (2015)
Data Resource Profile: Clinical Practice Research Datalink (CPRD)
Emily Herrett et al.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2015)
Defining Disease Phenotypes Using National Linked Electronic Health Records: A Case Study of Atrial Fibrillation
Katherine I. Morley et al.
PLOS ONE (2014)
Simple Risk Model Predicts Incidence of Atrial Fibrillation in a Racially and Geographically Diverse Population: the CHARGE-AF Consortium
Alvaro Alonso et al.
JOURNAL OF THE AMERICAN HEART ASSOCIATION (2013)
A Clinical Risk Score for Atrial Fibrillation in a Biracial Prospective Cohort (from the Atherosclerosis Risk In Communities [ARIC] Study)
Alanna M. Chamberlain et al.
AMERICAN JOURNAL OF CARDIOLOGY (2011)
Development of a risk score for atrial fibrillation (Framingham Heart Study): a community-based cohort study
Renate B. Schnabel et al.
LANCET (2009)
Pulse pressure and risk of new-onset atrial fibrillation
Gary F. Mitchell et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2007)
Contribution of atrial fibrillation to incidence and outcome of ischemic stroke - Results from a population-based study
C Marini et al.
STROKE (2005)
Characteristics, outcome, and care of stroke associated with atrial fibrillation in Europe - Data from a multicenter multinational hospital-based registry (the European Community Stroke Project)
M Lamassa et al.
STROKE (2001)
Share Paper
