Nathan Kim

1.1k citations
42 papers · 588 indexed · h-index 13

Nathan Kim

39 papers receiving 583 citations

Peers

Nathan Kim
Comparison fields: 5 of 89
  • Rehabilitation 156
  • Neurology 92
  • Neurology 89
  • Radiation 44
  • Geriatrics and Gerontology 19
Replace Justin Z. Wang with:
Justin Z. Wang Canada
Benoît Bihin Belgium
Jaime Díaz‐Guzmán Spain
Linda Miller United Kingdom
Michael G. Brandel United States
Saad Shafqat Pakistan
Jana Midelfart Hoff Norway
Ruth M. Pickering United Kingdom
Jennifer Mandzia Canada
Smriti Agarwal United Kingdom
Nathan Kim relative to Justin Z. Wang Canada Justin Z. Wang's profile →
Citations per field
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Justin Z. Wang · 1×
Citations per year

Countries citing papers authored by Nathan Kim

Since Specialization
Citations

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

Fields of papers citing papers by Nathan Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20243
2 20244
3 20244
4 20242
5 20235
6 20236
7 20237
8 20230
9 20226
10 202224
11 202113
12 20205
13 201922
14 20199
15 20188
16 20183
17 201846
18 201779
19
Constructing a Clinicopathologic Prognostic Model for Triple-Negative Breast Cancer
20173
20 201712

About Nathan Kim

Nathan Kim is a scholar working on Radiation, Health, Complementary and Manual Therapy, Rehabilitation and Radiology, Nuclear Medicine and Imaging, having authored 42 papers that have together received 588 indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (6 papers), Medical Imaging Techniques and Applications (4 papers), Spine and Intervertebral Disc Pathology (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Health disparities and outcomes (4 papers), Breast Cancer Treatment Studies (4 papers), Stroke Rehabilitation and Recovery (3 papers) and Transcranial Magnetic Stimulation Studies (3 papers). The work is most often cited by research in Rehabilitation (156 citations), Neurology (92 citations), Neurology (89 citations), Radiation (44 citations) and Geriatrics and Gerontology (19 citations). Nathan Kim has collaborated with scholars based in United States, Canada and New Zealand. Frequent co-authors include Tomoko Kitago, Jing Xu, Pablo Celnik, John W. Krakauer, Juan C. Cortés, Andreas R. Luft, Michelle D. Harran, Philippa Howden‐Chapman, Heidi M. Schambra and Benjamin Hertler. Their work appears in journals such as Physics in Medicine and Biology, Neurorehabilitation and neural repair, Journal of Epidemiology & Community Health, Journal of Applied Clinical Medical Physics and The International Journal of Spine Surgery.

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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