Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Impact of Myocardial Fibrosis in Patients With Symptomatic Severe Aortic Stenosis
2009545 citationsFrank Weidemann, Sebastian Herrmann et al.Circulationprofile →
Fabry disease revisited: Management and treatment recommendations for adult patients
2018401 citationsAlberto Ortíz, Dominique P. Germain et al.Molecular Genetics and Metabolismprofile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
citations ·
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Countries citing papers authored by Frank Weidemann
Since
Specialization
Citations
This map shows the geographic impact of Frank Weidemann'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 Frank Weidemann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Weidemann more than expected).
This network shows the impact of papers produced by Frank Weidemann. 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 Frank Weidemann. The network helps show where Frank Weidemann may publish in the future.
Co-authorship network of co-authors of Frank Weidemann
This figure shows the co-authorship network connecting the top 25 collaborators of Frank Weidemann.
A scholar is included among the top collaborators of Frank Weidemann 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 Frank Weidemann. Frank Weidemann is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Vardarli, Irfan, Christoph Rischpler, Ken Herrmann, & Frank Weidemann. (2020). Diagnosis and Screening of Patients with Fabry Disease. SHILAP Revista de lepidopterología.2 indexed citations
Ortíz, Alberto, Dominique P. Germain, Robert J. Desnick, et al.. (2018). Fabry disease revisited: Management and treatment recommendations for adult patients. Molecular Genetics and Metabolism. 123(4). 416–427.401 indexed citations breakdown →
4.
Liu, Danfeng, Kai Hu, Stefan Störk, et al.. (2014). Predictive value of systolic and diastolic strain rate for survival in cardiac amyloidosis patients with preserved ejection fraction. European Heart Journal. 35. 339–339.1 indexed citations
Čikeš, Maja, Volkmar Lange, Sven Lončarić, et al.. (2009). Does the aortic velocity profile in aortic stenosis patients reflect more than stenosis severity? The impact of myocardial fibrosis on aortic flow symmetry. European Heart Journal. 30. 605–605.2 indexed citations
9.
Weidemann, Frank, et al.. (2005). How to distinguish between physiological and pathological post-systolic-thickening. An experimental strain rate imaging study. European Heart Journal. 26. 329–329.1 indexed citations
10.
Weidemann, Frank, Christian Wacker, Alexandra Rauch, et al.. (2004). Ultrasonic strain rate imaging can predict the recovery of function after acute myocardial infarction and assess the transmurality of scar in chronic infarctions. Circulation. 110(17). 550–550.3 indexed citations
Mertens, Luc, Frank Weidemann, Bénédicte Eyskens, et al.. (2002). Quantification of regional right and left ventricular function by ultrasonic strain rate and strain indices after surgical repair of tetralogy of fallot. Cardiology in the Young. 12(1). 45–45.2 indexed citations
14.
Claus, Piet, Bart Bijnens, Frank Weidemann, et al.. (2001). Underlying mechanism of post-systolic thickening is this active contraction or a passive event? a one-dimensional mathematical model. European Heart Journal - Cardiovascular Imaging. 2.1 indexed citations
15.
Weidemann, Frank, Faizi Jamal, Tomasz Kukulski, et al.. (2001). Can ultrasonic strain rate imaging quantify the changes in systolic function during dobutamine infusion, b-blockade and atrial pacing? an experimental study. Journal of the American College of Cardiology. 37.1 indexed citations
16.
Dommke, Christoph, Frank Weidemann, Mirosław Kowalski, et al.. (2001). The importance of timing local versus global mechanical events in defining regional myocardial function? a ultrasonic strain rate strain imaging study. European Heart Journal. 22. 595–595.1 indexed citations
17.
Strotmann, Jörg, Frank Weidemann, Tomasz Kukulski, et al.. (2000). Regional systolic function changes in myocardial stunning during a dobutamine challenge. An experimental strain rate imaging study. Circulation. 102.8 indexed citations
18.
Weidemann, Frank, Faizi Jamal, Tomasz Kukulski, et al.. (2000). Can strain rate imaging characterize the spectrum of changes in regional systolic function induced by either dobutamine infusion, atrial pacing or beta-blockade ? A color Doppler myocardial imaging study. European Heart Journal - Cardiovascular Imaging. 1(2).7 indexed citations
19.
Kowalski, Mirosław, Tomasz Kukulski, Jan D’hooge, et al.. (2000). Can strain rate imaging be useful for evaluation regional right ventricular function ? A normal myocardial imaging study. European Heart Journal - Cardiovascular Imaging. 1(2).2 indexed citations
20.
Weidemann, Frank, Bart Bijnens, Tomasz Kukulski, et al.. (2000). Can color Doppler myocardial imaging identify chronically ischemic myocardium during dobutamine stress echocardiography ? An experiment study. Circulation. 102.
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.