Numero: a statistical framework to define multivariable subgroups in complex population-based datasets-Reference-Cited by-同舟云学术

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Numero: a statistical framework to define multivariable subgroups in complex population-based datasets

Published:2018-06-26 Issue:2 Volume:48 Page:369-374
ISSN:0300-5771
Container-title:International Journal of Epidemiology
language:en
Short-container-title:

Author:

Gao Song¹,Mutter Stefan¹,Casey Aaron¹,Mäkinen Ville-Petteri¹²³

Affiliation:

1. Heart Health Theme, South Australian Health and Medical Research Institute, Adelaide, SA, Australia

2. School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia

3. Computational Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland

Funder

EMBL Australia Partnership Program

South Australian Health and Medical Research Institute

Publisher

Oxford University Press (OUP)

Subject

General Medicine,Epidemiology

Link

http://academic.oup.com/ije/article-pdf/48/2/369/28479537/dyy113.pdf

Reference20 articles.

1. Plasma lipidomic profiles improve on traditional risk factors for the prediction of cardiovascular events in type 2 diabetes mellitus;Alshehry;Circulation,2016

2. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes;Ting;JAMA,2017

3. Machine learning approaches to personalize early prediction of asthma exacerbations;Finkelstein;Ann N Y Acad Sci,2017

4. Human disease classification in the postgenomic era: a complex systems approach to human pathobiology;Loscalzo;Mol Syst Biol,2007

5. Metabolic diversity of progressive kidney disease in 325 patients with type 1 diabetes (the FinnDiane Study);Mäkinen;J Proteome Res,2012

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