Deep biomarkers of aging are population-dependent. - sprookjes - yvandenbroek - TriplyDB

Deep biomarkers of aging are population-dependent.

Deep biomarkers of aging are population-dependent.

http://www.wikidata.org/entity/Q37361070

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The risks of biomarker-based epidemiology: Associations of circulating calcium levels with age, mortality, and frailty vary substantially across populations.Extracting biological age from biomedical data via deep learning: too much of a good thing?

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Deep biomarkers of aging are population-dependent.

http://www.wikidata.org/entity/Q37361070

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article científic

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article scientifique

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articolo scientifico

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artigo científico

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bilimsel makale

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scientific article published on 08 September 2016

@en

vedecký článok

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vetenskaplig artikel

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videnskabelig artikel

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vědecký článek

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name

Deep biomarkers of aging are population-dependent.

@en

Deep biomarkers of aging are population-dependent.

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type

label

Deep biomarkers of aging are population-dependent.

@en

Deep biomarkers of aging are population-dependent.

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prefLabel

Deep biomarkers of aging are population-dependent.

@en

Deep biomarkers of aging are population-dependent.

@nl

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Deep biomarkers of aging are population-dependent.

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Linda P Fried

http://www.w3.org/2001/XMLSchema#string

Luigi Ferrucci

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Vincent Morissette-Thomas

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DNA methylation age of human tissues and cell types

Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Dietary fiber and C-reactive protein: findings from national health and nutrition examination survey data.

Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled trials.

Genome-wide methylation profiles reveal quantitative views of human aging rates.

Inflammation, But Not Telomere Length, Predicts Successful Ageing at Extreme Old Age: A Longitudinal Study of Semi-supercentenarians

Deep biomarkers of human aging: Application of deep neural networks to biomarker development.

Trajectories of physiological dysregulation predicts mortality and health outcomes in a consistent manner across three populations.

Statistical distance as a measure of physiological dysregulation is largely robust to variation in its biomarker composition

Cross-population validation of statistical distance as a measure of physiological dysregulation during aging.

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2253-2255

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scholarly article

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10.18632/AGING.101034

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9

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