Danielle F. Pace
Impact in
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- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
Papers in
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- Congenital Heart Disease Studies 5
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- Soft Robotics and Applications 4
- Medical Imaging and Analysis 3
- Co-authors
- Stephen Aylward (5 shared papers)Marc Niethammer (4 shared papers)Andrei Irimia (2 shared papers)John D. Van Horn (2 shared papers)Paul Vespa (2 shared papers)David A. Hovda (1 shared paper)Bo Wang (1 shared paper)Marcel Prastawa (1 shared paper)
- Journals
- Frontiers in Cardiovascular Medicine (2 papers)Tomography (1 paper)Nature Medicine (1 paper)IEEE Transactions on Medical Imaging (1 paper)NeuroImage Clinical (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Danielle F. Pace
21 papers receiving 328 citations
Peers
Comparison fields: 5 of 53
- Radiology, Nuclear Medicine and Imaging 111
- Computer Vision and Pattern Recognition 103
- Health Informatics 4
- Neurology 34
- Epidemiology 74
Countries citing papers authored by Danielle F. Pace
This map shows the geographic impact of Danielle F. Pace'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 Danielle F. Pace with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle F. Pace more than expected).
Fields of papers citing papers by Danielle F. Pace
This network shows the impact of papers produced by Danielle F. Pace. 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 Danielle F. Pace. The network helps show where Danielle F. Pace may publish in the future.
Co-authors
The 25 scholars most cited alongside Danielle F. Pace, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 85 | |
| 2 | 2013 | 43 | |
| 3 | 2009 | 35 | |
| 4 | 2011 | 30 | |
| 5 | 2024 | 21 | |
| 6 | 2011 | 20 | |
| 7 | 2021 | 16 | |
| 8 | 2018 | 14 | |
| 9 | 2015 | 12 | |
| 10 | 2022 | 11 | |
| 11 | 2024 | 8 | |
| 12 | 2009 | 8 | |
| 13 | 2023 | 6 | |
| 14 | 2010 | 5 | |
| 15 | 2009 | 5 | |
| 16 | 2022 | 4 | |
| 17 | 2013 | 3 | |
| 18 | 2010 | 3 | |
| 19 | 2007 | 2 | |
| 20 | 2010 | 1 |
About Danielle F. Pace
Danielle F. Pace is a scholar working on Epidemiology, Biomedical Engineering, Surgery, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 21 papers that have together received 333 indexed citations. Recurring topics across this work include Cardiac Valve Diseases and Treatments (5 papers), Congenital Heart Disease Studies (5 papers), Medical Imaging Techniques and Applications (4 papers), Soft Robotics and Applications (4 papers), Surgical Simulation and Training (3 papers), Medical Image Segmentation Techniques (3 papers), Cardiac and Coronary Surgery Techniques (3 papers) and Medical Imaging and Analysis (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (111 citations), Computer Vision and Pattern Recognition (103 citations), Health Informatics (4 citations), Neurology (34 citations) and Epidemiology (74 citations). Danielle F. Pace has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Stephen Aylward, Marc Niethammer, Andrei Irimia, John D. Van Horn, Paul Vespa, David A. Hovda, Bo Wang, Marcel Prastawa, Ron Kikinis and Guido Gerig. Their work appears in journals such as Frontiers in Cardiovascular Medicine, Tomography, Nature Medicine, IEEE Transactions on Medical Imaging and NeuroImage Clinical.
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.