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Henry Völzke

Researcher at Greifswald University Hospital

Publications -  1093
Citations -  79204

Henry Völzke is an academic researcher from Greifswald University Hospital. The author has contributed to research in topics: Population & Study of Health in Pomerania. The author has an hindex of 115, co-authored 991 publications receiving 64260 citations. Previous affiliations of Henry Völzke include Group Health Cooperative & Umeå University.

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Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration

Raymond Noordam, +160 more
TL;DR: The authors perform genome-wide gene-by-sleep interaction analysis and find 49 previously unreported lipid loci when considering short or long total sleep time, contributing to the understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
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Thyroid Function Within the Reference Range and the Risk of Stroke: An Individual Participant Data Analysis

Layal Chaker, +46 more
TL;DR: Higher levels of TSH within the reference range may decrease the risk of stroke, highlighting the need for further research focusing on the clinical consequences associated with differences within thereference range of thyroid function.
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Stroke genetics informs drug discovery and risk prediction across ancestries

Aniket Mishra, +551 more
- 04 Jan 2022 - 
TL;DR: In this article , a cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses.
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Prior Shape Level Set Segmentation on Multistep Generated Probability Maps of MR Datasets for Fully Automatic Kidney Parenchyma Volumetry

TL;DR: A 3-D segmentation framework for fully automatic kidney parenchyma volumetry that uses Bayesian concepts for probability map generation and is able to recognize and exclude parenchymal cysts from the paren chymal volume.
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A fully automatic three-step liver segmentation method on LDA-based probability maps for multiple contrast MR images.

TL;DR: This work develops a fully automatic three-step 3D segmentation approach based upon a modified region growing approach and a further threshold technique that is modularized and can be applied for normal and fat accumulated liver tissue properties.