Jaemoon Koh

3.6k citations
93 papers · 2.6k · 1 hit paper · h-index 29

Impact in

  • Oncology top 2%
    • Cancer Immunotherapy and Biomarkers
    • Lung Cancer Research Studies
    • Cancer Cells and Metastasis
  • Immunology top 5%
    • Immune Cell Function and Interaction
    • Immunotherapy and Immune Responses
    • Immune cells in cancer

Papers in

    • Cancer Immunotherapy and Biomarkers 25
    • Lung Cancer Research Studies 8
    • Cancer Cells and Metastasis 7
    • Immune cells in cancer 14
    • Immune Cell Function and Interaction 13

Jaemoon Koh

90 papers receiving 2.6k citations

Hit Papers

Cell-intrinsic PD-L1 signaling drives immunosuppression by myeloid-derived suppressor cells through IL-6/Jak/Stat3 in PD-L1-high lung cancer 2025 · 25 citations
250Years since publication510152025

Peers

Jaemoon Koh
Comparison fields: 5 of 114
  • Oncology 1.5k
  • Immunology 687
  • Pulmonary and Respiratory Medicine 1.0k
  • Cancer Research 351
  • Genetics 117
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Citations per field
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Citations per year

Countries citing papers authored by Jaemoon Koh

Since Specialization
Citations

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

Fields of papers citing papers by Jaemoon Koh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015167
2 2015149
3 2015143
4 2015142
5 2016141
6 2015128
7 201595
8 201783
9 201778
10 201771
11 201760
12 201957
13 201653
14 201950
15 201747
16 201546
17 202046
18 201845
19 201744
20 202243

About Jaemoon Koh

Jaemoon Koh is a scholar working on Oncology, Immunology, Pulmonary and Respiratory Medicine, Surgery and Molecular Biology, having authored 93 papers that have together received 2.6k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (25 papers), Lung Cancer Treatments and Mutations (17 papers), Immune cells in cancer (14 papers), Immune Cell Function and Interaction (13 papers), Lung Cancer Research Studies (8 papers), Cancer Cells and Metastasis (7 papers), RNA modifications and cancer (6 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). The work is most often cited by research in Oncology (1.5k citations), Immunology (687 citations), Pulmonary and Respiratory Medicine (1.0k citations), Cancer Research (351 citations) and Genetics (117 citations). Jaemoon Koh has collaborated with scholars based in South Korea, Ethiopia and Puerto Rico. Frequent co-authors include Doo Hyun Chung, Yoon Kyung Jeon, Heounjeong Go, Sehui Kim, Moon‐Young Kim, Bhumsuk Keam, Young A Kim, Dohee Kwon, Tae Min Kim and Young Tae Kim. Their work appears in journals such as European Journal of Cancer, Lung Cancer, Clinical Cancer Research, Scientific Reports and BMC Pulmonary Medicine.

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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