Marcus Schreckenberg

1.5k total citations
14 papers, 525 citations indexed

About

Marcus Schreckenberg is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Marcus Schreckenberg has authored 14 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cardiology and Cardiovascular Medicine, 9 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Surgery. Recurrent topics in Marcus Schreckenberg's work include Cardiovascular Function and Risk Factors (10 papers), Cardiac Imaging and Diagnostics (7 papers) and Cardiac Valve Diseases and Treatments (6 papers). Marcus Schreckenberg is often cited by papers focused on Cardiovascular Function and Risk Factors (10 papers), Cardiac Imaging and Diagnostics (7 papers) and Cardiac Valve Diseases and Treatments (6 papers). Marcus Schreckenberg collaborates with scholars based in United States, Germany and Netherlands. Marcus Schreckenberg's co-authors include Georg Schummers, Andreas Franke, Peter Hanrath, Arno Bücker, Dierk Rulands, Wolfgang Schäfer, Markus Katoh, Harald P. Kühl, Christian Knackstedt and Luigi P. Badano and has published in prestigious journals such as Journal of the American College of Cardiology, JACC. Cardiovascular imaging and Journal of the American Society of Echocardiography.

In The Last Decade

Marcus Schreckenberg

12 papers receiving 510 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Marcus Schreckenberg United States 7 413 296 90 63 46 14 525
Georg Schummers Germany 11 830 2.0× 661 2.2× 152 1.7× 105 1.7× 75 1.6× 22 1.0k
Yu Horiuchi Japan 10 325 0.8× 89 0.3× 129 1.4× 43 0.7× 104 2.3× 51 515
Rak Kyeong Choi South Korea 13 428 1.0× 131 0.4× 182 2.0× 70 1.1× 89 1.9× 45 592
Fabian Barbieri Austria 12 232 0.6× 134 0.5× 102 1.1× 45 0.7× 65 1.4× 70 363
Liza P Moorman United States 7 368 0.9× 62 0.2× 137 1.5× 35 0.6× 35 0.8× 13 484
Valentina Volpato Italy 16 532 1.3× 361 1.2× 160 1.8× 142 2.3× 113 2.5× 38 709
Nilesh Sutaria United Kingdom 14 380 0.9× 96 0.3× 114 1.3× 186 3.0× 114 2.5× 32 487
Christopher Occleshaw New Zealand 11 420 1.0× 244 0.8× 154 1.7× 123 2.0× 92 2.0× 26 576
Eitan Abergel Israel 8 84 0.2× 103 0.3× 73 0.8× 123 2.0× 121 2.6× 16 330
Arash Mokhtari Sweden 10 277 0.7× 150 0.5× 65 0.7× 17 0.3× 38 0.8× 26 342

Countries citing papers authored by Marcus Schreckenberg

Since Specialization
Citations

This map shows the geographic impact of Marcus Schreckenberg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marcus Schreckenberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcus Schreckenberg more than expected).

Fields of papers citing papers by Marcus Schreckenberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcus Schreckenberg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marcus Schreckenberg. The network helps show where Marcus Schreckenberg may publish in the future.

Co-authorship network of co-authors of Marcus Schreckenberg

This figure shows the co-authorship network connecting the top 25 collaborators of Marcus Schreckenberg. A scholar is included among the top collaborators of Marcus Schreckenberg based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marcus Schreckenberg. Marcus Schreckenberg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Cotella, Juan Ignacio, Karima Addetia, Tatsuya Miyoshi, et al.. (2024). Optimización de la interpretación de ecocardiogramas utilizando machine learning en el estudio WASE. 92(1). 5–14.
2.
Cotella, Juan Ignacio, Alexandra Clément, Michele Tomaselli, et al.. (2024). Three-Dimensional Transthoracic Echocardiography for Semiautomated Analysis of the Tricuspid Annulus: Validation and Normal Values. Journal of the American Society of Echocardiography. 38(1). 33–43.e3. 2 indexed citations
3.
Morbach, Caroline, Götz Gelbrich, Marcus Schreckenberg, et al.. (2023). Population data–based federated machine learning improves automated echocardiographic quantification of cardiac structure and function: the Automatisierte Vermessung der Echokardiographie project. European Heart Journal - Digital Health. 5(1). 77–88. 2 indexed citations
4.
Mor‐Avi, Victor, Marcus Schreckenberg, Karima Addetia, et al.. (2023). Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency. The International Journal of Cardiovascular Imaging. 39(12). 2507–2516.
5.
Cotella, Juan Ignacio, et al.. (2023). Semiautomated Quantification of the Tricuspid Annulus Using Three-Dimensional Echocardiography. Journal of the American Society of Echocardiography. 36(11). 1215–1217. 1 indexed citations
6.
Singh, Amita, Jimmy Su, Jean‐Michel Rouet, et al.. (2022). A Novel Approach for Semiautomated Three-Dimensional Quantification of Mitral Regurgitant Volume Reflects a More Physiologic Approach to Mitral Regurgitation. Journal of the American Society of Echocardiography. 35(9). 940–946. 11 indexed citations
7.
Narang, Akhil, Victor Mor‐Avi, Marcus Schreckenberg, et al.. (2020). Virtual Reality Analysis of Three-Dimensional Echocardiographic and Cardiac Computed Tomographic Data Sets. Journal of the American Society of Echocardiography. 33(11). 1306–1315. 14 indexed citations
8.
Lang, Roberto M., Karima Addetia, Tatsuya Miyoshi, et al.. (2020). Use of Machine Learning to Improve Echocardiographic Image Interpretation Workflow: A Disruptive Paradigm Change?. Journal of the American Society of Echocardiography. 34(4). 443–445. 18 indexed citations
9.
Verdonschot, Job A.J., Jort J. Merken, Hans‐Peter Brunner‐La Rocca, et al.. (2019). Value of Speckle Tracking–Based Deformation Analysis in Screening Relatives of Patients With Asymptomatic Dilated Cardiomyopathy. JACC. Cardiovascular imaging. 13(2). 549–558. 39 indexed citations
10.
Knackstedt, Christian, Sebastiaan C.A.M. Bekkers, Georg Schummers, et al.. (2015). Fully Automated Versus Standard Tracking of Left Ventricular Ejection Fraction and Longitudinal Strain. Journal of the American College of Cardiology. 66(13). 1456–1466. 180 indexed citations
11.
Skornitzke, Stephan, Georg Schummers, Marcus Schreckenberg, et al.. (2015). Mass-spring systems for simulating mitral valve repair using 3D ultrasound images. Computerized Medical Imaging and Graphics. 45. 26–35. 5 indexed citations
12.
Franke, Andreas, Marcus Schreckenberg, Georg Schummers, et al.. (2012). Beat to beat 3-dimensional intracardiac echocardiography: theoretical approach and practical experiences. International journal of cardiac imaging. 29(4). 753–764. 3 indexed citations
13.
Eyer, Florian, Marcus Schreckenberg, Kristina Adorjan, et al.. (2011). Carbamazepine and Valproate as Adjuncts in the Treatment of Alcohol Withdrawal Syndrome: A Retrospective Cohort Study. Alcohol and Alcoholism. 46(2). 177–184. 31 indexed citations
14.
Kühl, Harald P., Marcus Schreckenberg, Dierk Rulands, et al.. (2004). High-resolution transthoracic real-time three-dimensional echocardiography. Journal of the American College of Cardiology. 43(11). 2083–2090. 219 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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