Nathan Kim

1.1k citations
43 papers · 624 · h-index 13

Impact in

    • Stroke Rehabilitation and Recovery
  • Neurology top 10%
    • Transcranial Magnetic Stimulation Studies
    • Botulinum Toxin and Related Neurological Disorders

Papers in

Nathan Kim

39 papers receiving 620 citations

Peers

Nathan Kim
Comparison fields: 5 of 86
  • Rehabilitation 131
  • Neurology 76
  • Geriatrics and Gerontology 19
  • Neurology 55
  • Cognitive Neuroscience 76
Replace Iuri Santana Neville with:
Iuri Santana Neville Brazil
Yuxiao Li China
Benoît Bihin Belgium
Jaime Díaz‐Guzmán Spain
Nilay Şahin Türkiye
Kathryn Lang United States
Nick Gebruers Belgium
Nolan J. Brown United States
Ruth M. Pickering United Kingdom
Zalmaï Hakimi United Kingdom
Nathan Kim relative to Iuri Santana Neville Brazil Iuri Santana Neville's profile →
Citations per field
00.5×1.5×1.9×
Iuri Santana Neville · 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-authors

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

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201797
2 201783
3 202270
4 201847
5 201934
6 201930
7 202229
8 201627
9 201922
10 201919
11 202113
12 202213
13 201712
14 201711
15 201810
16 20199
17 20199
18 20208
19 20188
20 20237

About Nathan Kim

Nathan Kim is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging, Surgery, Radiation and Cancer Research, having authored 43 papers that have together received 624 indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (4 papers), Advanced Radiotherapy Techniques (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Transcranial Magnetic Stimulation Studies (3 papers), Stroke Rehabilitation and Recovery (3 papers), COVID-19 Clinical Research Studies (2 papers), Spine and Intervertebral Disc Pathology (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Rehabilitation (131 citations), Neurology (76 citations), Geriatrics and Gerontology (19 citations), Neurology (55 citations) and Cognitive Neuroscience (76 citations). Nathan Kim has collaborated with scholars based in United States, Canada and New Zealand. Frequent co-authors include Andreas R. Luft, John W. Krakauer, Michelle D. Harran, Pablo Celnik, Jing Xu, Juan C. Cortés, Tomoko Kitago, Philippa Howden‐Chapman, Heidi M. Schambra and David Ormandy. 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 Advanced Healthcare Materials.

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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