Jennifer A. Steeden

2.0k citations
71 papers · 1.4k indexed · h-index 21

Jennifer A. Steeden

68 papers receiving 1.4k citations

Peers

Jennifer A. Steeden
Comparison fields: 5 of 106
  • Cardiology and Cardiovascular Medicine 655
  • Radiology, Nuclear Medicine and Imaging 573
  • Behavioral Neuroscience 53
  • Nephrology 95
  • Health Informatics 16
Replace Matthias Hammon with:
Matthias Hammon Germany
Marat Slessarev Canada
Alois M. Sprinkart Germany
Kenneth C. Bilchick United States
Yasumasa Tsukamoto Japan
Pankaj Garg United Kingdom
Domenico De Santis Italy
Leonard M. Zir United States
Richard L. Kirkeeide United States
Jennifer A. Steeden relative to Matthias Hammon Germany Matthias Hammon's profile →
Citations per field
00.5×3.9×
Matthias Hammon · 1×
Citations per year

Countries citing papers authored by Jennifer A. Steeden

Since Specialization
Citations

This map shows the geographic impact of Jennifer A. Steeden'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 Jennifer A. Steeden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jennifer A. Steeden more than expected).

Fields of papers citing papers by Jennifer A. Steeden

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jennifer A. Steeden. 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 Jennifer A. Steeden. The network helps show where Jennifer A. Steeden may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jennifer A. Steeden, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jennifer A. Steeden Line = papers co-authored together Jennifer A. Steeden links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20245
2 20240
3 20235
4 20232
5
Machine learning in Magnetic Resonance Imaging:image reconstruction
202137
6
Rapid whole-heart CMR with single volume super-resolution
202051
7 202058
8
Real-time Cardiovascular MR with Spatio-temporal De-aliasing using Deep Learning - Proof of Concept in Congenital Heart Disease
20181
9 201735
10 201517
11 201510
12 201538
13 201431
14 201317
15 201218
16 201244
17 201240
18 201124
19 201143
20 20106

About Jennifer A. Steeden

Jennifer A. Steeden is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Behavioral Neuroscience, having authored 71 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (41 papers), Cardiovascular Function and Risk Factors (19 papers), Atomic and Subatomic Physics Research (17 papers), Cardiac Imaging and Diagnostics (16 papers), Congenital Heart Disease Studies (13 papers), Cardiovascular Health and Disease Prevention (11 papers), Medical Imaging Techniques and Applications (10 papers) and Pulmonary Hypertension Research and Treatments (8 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (655 citations), Radiology, Nuclear Medicine and Imaging (573 citations) and Behavioral Neuroscience (53 citations). Jennifer A. Steeden has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Vivek Muthurangu, Andrew M. Taylor, Andreas Hauptmann, Simon Arridge, David Atkinson, Michael A. Quail, Daniel Knight, Felix Lucka, Bejal Pandya and Patrick Segers. Their work appears in journals such as PLoS ONE, The Journal of Physiology and Scientific Reports.

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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