Associated factors of white matter hyperintensity volume: a machine-learning approach

Associated factors of white matter hyperintensity volume: a machine-learning approach

Abstract To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we used a data-driven machine-learning approach. We analysed two independent cohorts (KORA and SHIP). WMH volumes were derived from cMRI-images...

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Bibliographic Details
Main Authors: Sergio Grosu, Susanne Rospleszcz, Felix Hartmann, Mohamad Habes, Fabian Bamberg, Christopher L. Schlett, Franziska Galie, Roberto Lorbeer, Sigrid Auweter, Sonja Selder, Robin Buelow, Margit Heier, Wolfgang Rathmann, Katharina Mueller-Peltzer, Karl-Heinz Ladwig, Hans J. Grabe, Annette Peters, Birgit B. Ertl-Wagner, Sophia Stoecklein
Format: Article
Language:English
Published: Nature Publishing Group 2021-01-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-81883-4

Internet

https://doi.org/10.1038/s41598-021-81883-4

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