The scientist’s investigation covers issues in Internal medicine, Diabetes mellitus, Prospective cohort study, Genome-wide association study and Endocrinology. Internal medicine is a component of his Relative risk, Odds ratio, Vascular disease, Risk factor and Cholesterol studies. The Diabetes mellitus study combines topics in areas such as Stroke and Mortality rate.
His work in Prospective cohort study tackles topics such as Hazard ratio which are related to areas like Cause of death and Immunology. His Genome-wide association study study is associated with Genetics. His research in Genetic association intersects with topics in Common disease-common variant, Quantitative trait locus and Angina.
His primary areas of study are Internal medicine, Cardiology, Stroke, Disease and Prospective cohort study. His work investigates the relationship between Internal medicine and topics such as Endocrinology that intersect with problems in Allele. His studies in Stroke integrate themes in fields like Surgery and Cohort.
His Disease research is multidisciplinary, incorporating elements of Genome-wide association study, Epidemiology, Bioinformatics, Blood pressure and Meta-analysis. His work deals with themes such as Genetics, Risk factor, MEDLINE and Confidence interval, which intersect with Meta-analysis. His Prospective cohort study research is multidisciplinary, incorporating perspectives in Immunology, Myocardial infarction, Framingham Risk Score and Cohort study.
Emanuele Di Angelantonio focuses on Internal medicine, Disease, Prospective cohort study, Genetics and Mendelian randomization. The concepts of his Internal medicine study are interwoven with issues in Endocrinology and Cardiology. His Disease study also includes fields such as
The Prospective cohort study study combines topics in areas such as Biobank, Framingham Risk Score, Hazard ratio, Typing and Cohort. His work on Blood cell as part of general Genetics study is frequently connected to TMPRSS6, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Genome-wide association study study incorporates themes from Computational biology, Genetic association and Bioinformatics.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Diabetes mellitus, fasting glucose, and risk of cause-specific death.
Sreenivasa Rao Kondapally Seshasai;Stephen Kaptoge;Alexander Thompson;Emanuele Di Angelantonio.
The New England Journal of Medicine (2011)
Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents
Emanuele Di Angelantonio;Shilpa N Bhupathiraju;David Wormser;Pei Gao;Pei Gao.
The Lancet (2016)
Association of Dietary, Circulating, and Supplement Fatty Acids With Coronary Risk: A Systematic Review and Meta-analysis
Rajiv Chowdhury;Samantha Warnakula;Setor Kunutsor;Francesca Crowe.
Annals of Internal Medicine (2014)
C-Reactive Protein, Fibrinogen, and Cardiovascular Disease Prediction
Stephen Kaptoge;Emanuele Di Angelantonio;Lisa Pennells;Angela M. Wood.
The New England Journal of Medicine (2012)
The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease
William J. Astle;Heather Elding;Heather Elding;Tao Jiang;Dave Allen.
Cell (2016)
Association of apolipoprotein E genotypes with lipid levels and coronary risk.
Anna M. Bennet;Emanuele Di Angelantonio;Zheng Ye;Frances Wensley.
JAMA (2007)
Genetic associations with valvular calcification and aortic stenosis.
George Thanassoulis;George Thanassoulis;Catherine Y. Campbell;David S. Owens;J. Gustav Smith;J. Gustav Smith.
The New England Journal of Medicine (2013)
Interleukin-6 receptor pathways in coronary heart disease: a collaborative meta-analysis of 82 studies
Nadeem Sarwar;Adam S. Butterworth;Daniel F. Freitag;John Gregson.
web science (2012)
Prevalence of Depression and Depressive Symptoms Among Resident Physicians: A Systematic Review and Meta-analysis.
Douglas A. Mata;Marco A. Ramos;Narinder Bansal;Rida Khan.
JAMA (2015)
Hypertension in India: A systematic review and meta-analysis of prevalence, awareness, and control of hypertension
Raghupathy Anchala;Nanda K. Kannuri;Hira Pant;Hassan Khan.
Journal of Hypertension (2014)
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