Showing results (81-90 of 240) with videos related to
Sort By:
Pageof 24
International Journal of Epidemiology|July 28, 2006
Fibrinogen and coronary heart disease: test of causality by 'Mendelian randomization'Bernard Keavney, John Danesh, Sarah Parish, et al.Plos One|February 2, 2013
Common variation neighbouring micro-RNA 22 is associated with increased left ventricular massAndrew R Harper, Bongani M Mayosi, Antony Rodriguez, et al.Scientific Reports|January 31, 2018
Phase Coexistence and Kinetic Arrest in the Magnetostructural Transition of the Ordered Alloy FeRhDavid J Keavney, Yongseong Choi, Martin V Holt, et al.Diabetologia|August 1, 1995
UK prospective diabetes study (UKPDS) 14: association of angiotensin-converting enzyme insertion/deletion polymorphism with myocardial infarction in NIDDMB D Keavney, C R Dudley, I M Stratton, et al.Plos One|March 11, 2017
4D flow MRI assessment of right atrial flow patterns in the normal heart - influence of caval vein arrangement and implications for the patent foramen ovaleJehill D Parikh, Jayant Kakarla, Bernard Keavney, et al.Journal of Medical Genetics|June 7, 2005
A rare variant of the leptin gene has large effects on blood pressure and carotid intima-medial thickness: a study of 1428 individuals in 248 familiesN Gaukrodger, B M Mayosi, H Imrie, et al.JAMA|June 19, 2008
Association of cholesteryl ester transfer protein genotypes with CETP mass and activity, lipid levels, and coronary riskAlexander Thompson, Emanuele Di Angelantonio, Nadeem Sarwar, et al.BMC Cardiovascular Disorders|November 20, 2020
Global prevalence of congenital heart disease in school-age children: a meta-analysis and systematic reviewYingjuan Liu, Sen Chen, Liesl Zühlke, et al.Atherosclerosis|August 5, 2008
Novel genetic variants linked to coronary artery disease by genome-wide association are not associated with carotid artery intima-media thickness or intermediate risk phenotypesM S Cunnington, B M Mayosi, D H Hall, et al.Scientific Reports|August 14, 2023
Predicting congenital renal tract malformation genes using machine learningMitra Kabir, Helen M Stuart, Filipa M Lopes, et al.Pageof 24