Daniel Kim

1.2k citations
70 papers · 822 · h-index 15

Impact in

Papers in

Daniel Kim

62 papers receiving 816 citations

Peers

Daniel Kim
Comparison fields: 5 of 63
  • Radiology, Nuclear Medicine and Imaging 524
  • Cardiology and Cardiovascular Medicine 160
  • Computational Mathematics 4
  • Ophthalmology 21
  • Computational Mechanics 50
Replace Peter Koken with:
Peter Koken Germany
Davide Piccini Switzerland
Peter Speier Germany
Sohae Chung United States
Sathya Vijayakumar United States
Jason Grimes United States
Olivier Jaubert United Kingdom
Geert Springeling Netherlands
G.J. Klein United States
Sascha Krueger Germany
Daniel Kim relative to Peter Koken Germany Peter Koken's profile →
Citations per field
00.5×4.2×
Peter Koken · 1×
Citations per year

Countries citing papers authored by Daniel Kim

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Kim. 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 Daniel Kim. The network helps show where Daniel Kim may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel Kim, 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 Daniel Kim Line = papers co-authored together Daniel Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012184
2 201454
3 202040
4 201739
5 199733
6 202031
7 202125
8 202025
9 202119
10 202119
11 201218
12 201817
13 201316
14 202016
15 202115
16 201813
17 201113
18 200313
19 202413
20 202012

About Daniel Kim

Daniel Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Biomedical Engineering, Atomic and Molecular Physics, and Optics and Computer Vision and Pattern Recognition, having authored 70 papers that have together received 822 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (39 papers), Cardiac Imaging and Diagnostics (20 papers), Cardiac Valve Diseases and Treatments (5 papers), Cardiac Arrhythmias and Treatments (5 papers), Cardiovascular Function and Risk Factors (5 papers), Atomic and Subatomic Physics Research (4 papers), Medical Imaging Techniques and Applications (4 papers) and Cardiac pacing and defibrillation studies (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (524 citations), Cardiology and Cardiovascular Medicine (160 citations), Computational Mathematics (4 citations), Ophthalmology (21 citations) and Computational Mechanics (50 citations). Daniel Kim has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Edward DiBella, Ganesh Adluru, Ruth Lim, Monvadi B. Srichai, Ricardo Otazo, James Carr, Daniel K. Sodickson, Li Feng, Daniel Lee and Wilson King. Their work appears in journals such as Magnetic Resonance in Medicine, NMR in Biomedicine, Radiology Cardiothoracic Imaging, Journal of Magnetic Resonance Imaging and Journal of Cardiovascular Electrophysiology.

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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