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Benjamin Meder

Researcher at Heidelberg University

Publications -  226
Citations -  9623

Benjamin Meder is an academic researcher from Heidelberg University. The author has contributed to research in topics: Dilated cardiomyopathy & Medicine. The author has an hindex of 49, co-authored 198 publications receiving 7530 citations. Previous affiliations of Benjamin Meder include University Hospital Heidelberg & Stanford University.

Papers
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Journal ArticleDOI

Postcardiac injury syndrome after cardiac implantable electronic device implantation.

TL;DR: The data show that PCIS is a rare complication after CIED implantation and occurs more frequently in patients with DCM and those with RA lead implantation.
Journal ArticleDOI

A genetic variant alters the secondary structure of the lncRNA H19 and is associated with dilated cardiomyopathy

TL;DR: In this paper, the effect of single nucleotide polymorphisms (SNPs) on the structure of lncRNAs was investigated in the context of dilated cardiomyopathy and showed that SNPs affecting such structures may explain hidden genetic variance not accounted for through genome wide association studies.
Patent

Epigenetic signatures as marker for cardiomyopathies and myocardial insufficiencies

TL;DR: The use of DNA methylation profiles of patient samples for the diagnosis, prognosis and/or therapy monitoring of a heart disease in a patient is discussed in this paper, where the DNA methylations profile of the patient sample is compared with the DNA profiles of a control sample.
Patent

Complex sets of mirnas as non-invasive biomarkers for dilated cardiomyopathy

TL;DR: In this article, non-invasive methods, kits and means for diagnosing and/or prognosing of dilated cardiomyopathy in a body fluid sample from a subject.
Proceedings ArticleDOI

Data-driven computational models of heart anatomy, mechanics and hemodynamics: An integrated framework

TL;DR: This work proposes an integrated framework for multi-physics heart modeling based on imaging data that relies on efficient machine learning methods to estimate an accurate and comprehensive model of patient's anatomy from MRI.