So‐Woon Kim

917 citations
44 papers · 540 · h-index 10

Impact in

    • Cancer Immunotherapy and Biomarkers
    • HER2/EGFR in Cancer Research
    • Cutaneous Melanoma Detection and Management
  • Biophysics top 10%
    • Cell Image Analysis Techniques

Papers in

    • Cancer Immunotherapy and Biomarkers 6
    • Cutaneous Melanoma Detection and Management 2

So‐Woon Kim

39 papers receiving 534 citations

Peers

So‐Woon Kim
Comparison fields: 5 of 88
  • Oncology 124
  • Biophysics 28
  • Obstetrics and Gynecology 29
  • Cancer Research 47
  • Structural Biology 4
Replace Nobuki Nakamura with:
Nobuki Nakamura Japan
Cinzia Melchiorri Italy
Kristen E. Muller United States
W Famulski Poland
Joshua Li Hong Kong
Piotr Donizy Poland
Л. В. Спирина Russia
Mingyuan He China
Yajue Huang United States
Na Cheng China
So‐Woon Kim relative to Nobuki Nakamura Japan Nobuki Nakamura's profile →
Citations per field
00.5×4.1×
Nobuki Nakamura · 1×
Citations per year

Countries citing papers authored by So‐Woon Kim

Since Specialization
Citations

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

Fields of papers citing papers by So‐Woon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016308
2 202122
3 202021
4 202116
5 202415
6 202013
7 201812
8 202210
9 202010
10 201810
11 20209
12 20217
13 20157
14 20207
15 20187
16 20226
17 20206
18 20215
19 20205
20 20215

About So‐Woon Kim

So‐Woon Kim is a scholar working on Oncology, Surgery, Molecular Biology, Pathology and Forensic Medicine and Pulmonary and Respiratory Medicine, having authored 44 papers that have together received 540 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (6 papers), Lymphoma Diagnosis and Treatment (4 papers), Ovarian cancer diagnosis and treatment (3 papers), Endometrial and Cervical Cancer Treatments (3 papers), AI in cancer detection (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Cutaneous Melanoma Detection and Management (2 papers) and CNS Lymphoma Diagnosis and Treatment (2 papers). The work is most often cited by research in Oncology (124 citations), Biophysics (28 citations), Obstetrics and Gynecology (29 citations), Cancer Research (47 citations) and Structural Biology (4 citations). So‐Woon Kim has collaborated with scholars based in South Korea and United States. Frequent co-authors include Jin Roh, Chan-Sik Park, Kiyong Na, Hyun Soo Kim, Min‐Hee Ryu, Sangjoon Choi, Sung‐Im Do, Young Soo Park, Young-Soo Park and Hye Seung Lee. Their work appears in journals such as Anticancer Research, Journal of Clinical Oncology, Modern Pathology, International Journal of Clinical and Experimental Pathology and Blood.

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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