Menu:

Homepage of Marcus Vollmer

Marcus Vollmer

Ongoing Research Projects

Clinical sepsis research | SepsisDialog

Our research is focussed on the new sepsis definition, medication during the acute phase of severe sepsis and septic show and on computer assisted sepsis diagnostics.

Sreening for Leiomyosarcoma | DKSM

About 50% of all leiomyosarcoma were treated according to the leiomyoma treatment protocol, because malignancy was not suspected at the time of surgery. We are working on a screening system to reduce the number of inadequate surgery using data from the DKSM (German Clinical Center of Excellence for Genital Sarcomas and Mixed Tumors) and outpatient study center.

Cardiovascular diseases | DZHK

We are currently screening and evaluating data of the orthostatic test from the cross-sectional study SHiP (Study of Health in Pomerania). In particular we are looking for clinical marker of the coronary artery disease.

Smell Capacity Disorders

In cooperation with Dr. Beule (ENT) we are working on the prevalence and aetiology of smell capacity disorders. We use data from the SHiP study.

Endoscopic Third Ventriculostomy

In cooperation with Dr. Marx (Neurosurgery) we are working on a score system for predicting the success of the ETV which incorporates liquor data.

Heart Rate Variability and Annotation/Segmentation of the ECG

  • Robust Detection of Heart Beats in Multimodal Data: the PhysioNet/Computing in Cardiology Challenge 2014 (see challenge); UPDATE: 1st place in Phase I, Phase II: 2nd, Phase III: 5th. Abstract, QRS Detection (Comic).
  • Measures of Heart Rate Variability / Use of relative RR Intervals (see MarcusVollmer.github.io/HRV)
  • AF Classification from a short single lead ECG recording: the PhysioNet/Computing in Cardiology Challenge 2017 (see challenge);
  • ECG Working Group

Publications

Sodmann P, Vollmer M, Nath N, Kaderali L (2018)
A Convolutional Neural Network for ECG Annotation as the Basis for Classification of Cardiac Rhythms
Physiological Measurement, 2018; - Volume Publish Ahead of Print - Issue - p.

Scheer CS, Fuchs C, Gründling M, Vollmer M, Bast J, Bohnert JA, Zimmermann K, Hahnenkamp K, Rehberg S, Kuhn SO (2018)
Impact of antibiotic administration on blood culture positivity at the beginning of sepsis: a prospective clinical cohort study
Clinical Microbiology and Infection, 2018; - Volume Publish Ahead of Print - Issue - p.

Scheer CS, Kuhn S, Fuchs C, Vollmer M, Modler M, Brunkhorst F, Shankar-Hari M, Hahnenkamp K, Gründling M, Rehberg S. (2018)
Do Sepsis-3 criteria facilitate earlier recognition of sepsis and septic shock? A retrospective cohort study
Shock, 2018; - Volume Publish Ahead of Print - Issue - p.

Vollmer M, Sodmann P, Caanitz L, Nath N, Kaderali L (2017)
Can Supervised Learning Be Used to Classify Cardiac Rhythms?
Computing in Cardiology (CinC), 2017; Vol 44; ISSN: 2325-887X; DOI:10.22489/CinC.2017.347-176

Vollmer M (2017)
Noise Resistance of Several Top-Scored Heart Beat Detectors
Computing in Cardiology (CinC), 2017; Vol 44; ISSN: 2325-887X; DOI:10.22489/CinC.2017.182-178

Vollmer M (2017)
Arrhythmia Classification in Long-Term Data Using Relative RR Intervals
Computing in Cardiology (CinC), 2017; Vol 44; ISSN: 2325-887X; DOI:10.22489/CinC.2017.213-185

Fuchs C, Wauschkuhn S, Scheer CS, Vollmer M, Meissner K, Kuhn S, Hahnenkamp K, et al. (2017)
Continuing chronic beta-blockade in the acute phase of severe sepsis and septic shock is associated with decreased mortality rates up to 90 days
British Journal of Anaesthesia, 2017; 119(4), p 616-625.

Scheer CS, Fuchs C, Kuhn S, Vollmer M, Rehberg S, Meissner K, et al. (2017)
Quality Improvement Initiative for Severe Sepsis and Septic Shock Reduces 90-Day Mortality: A 7.5-Year Observational Study
Critical Care Medicine, 2017; 45(2), p 241-252.

Vollmer M (2015)
A Robust, Simple and Reliable Measure of Heart Rate Variability using Relative RR Intervals
Computing in Cardiology Conference (CinC), 2015; Nice, France; ISSN: 2325-8861; p 609-612.

Vollmer M (2014)
Robust Detection of Heart Beats using Dynamic Thresholds and Moving Windows
Computing in Cardiology Conference (CinC), 2014; Cambridge, MA; ISSN: 2325-8861; p 569-572.

Teaching Experience

Talks and more

Estimation of Sample Size and Power for Dunnetts Testing Setups with Unequal Effect Sizes

Adaptive Designs and Mutiple Testing Procedures (Bremen 2018)

Can Supervised Learning be used to Classify Cardiac Rhythms?

Computing in Cardiology (Rennes 2017)

Noise Resistance of Several Top-Scored Heart Beat Detectors

Computing in Cardiology (Rennes 2017)

A Robust, Simple and Reliable Measure of Heart Rate Variability using Relative RR Intervals

Computing in Cardiology (Nice 2015)

Robust Detection of Heart Beats using Dynamic Thresholds and Moving Windows
PhysioNet/Computing in Cardiology Challenge 2014
Results: 1st place in Phase I, Phase II: 2nd, Phase III: 5th.preprints: http://www.cinc.org/archives/2014/

Computing in Cardiology (Cambridge 2014)

Randomized Model Selection as a Model Building Strategy in Stepwise Logistic Regression

Potsdam Conference on Structural Inference in Statistics 2013

Die USA haben 25-Cent-Münzen. Warum hat der Euro keine?

Kinder- und Jugenduni Greifswald 2013

A circular distribution family and tests for independence

Copulae in mathematical and quantitative finance (Kraków 2012)

A new Independence Test for continuous variables

Computing & Statistics (ERCIM'11) (London 2011)

GRaP Independence Test

17. DStatG Nachwuchsworkshop (Leipzig 2011)

GRaP Independence Test (Animationen nur im Vollbildmodus)

Weihnachtskolloquium 2010


Software

HRVTool

HRVTool.app for Matlab
Please visit the project page on GitHub marcusvollmer.github.io/HRV. The application is licensed under MIT license (use, copy, modify, merge, publish, distribute, sublicense, and/or sell).

DataDownload

DataDownload.app for Matlab
DataDownload for as a standalone executable upon request.

LiveRecording

LiveRecording.app for Matlab
LiveRecording as a standalone executable upon request.

R-Helper-Functions

R helper functions
R functions for summary statistics and statistical analysis.