Ka‐Won Kang

1.1k total citations · 1 hit paper
70 papers, 754 citations indexed

About

Ka‐Won Kang is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Ka‐Won Kang has authored 70 papers receiving a total of 754 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Hematology, 28 papers in Molecular Biology and 21 papers in Oncology. Recurrent topics in Ka‐Won Kang's work include Multiple Myeloma Research and Treatments (15 papers), Protein Degradation and Inhibitors (10 papers) and Lymphoma Diagnosis and Treatment (9 papers). Ka‐Won Kang is often cited by papers focused on Multiple Myeloma Research and Treatments (15 papers), Protein Degradation and Inhibitors (10 papers) and Lymphoma Diagnosis and Treatment (9 papers). Ka‐Won Kang collaborates with scholars based in South Korea, Japan and United States. Ka‐Won Kang's co-authors include Yong Park, Sunghoi Hong, Hyun Koo Kim, Yeonho Choi, Byeong Hyeon Choi, Hyesun Jeong, Hyunku Shin, Min-Sung Kang, Seunghyun Oh and Soonwoo Hong and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Ka‐Won Kang

60 papers receiving 747 citations

Hit Papers

Early-Stage Lung Cancer D... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ka‐Won Kang South Korea 12 385 181 137 130 125 70 754
Yuanji Xu China 17 377 1.0× 130 0.7× 190 1.4× 211 1.6× 11 0.1× 70 893
Byeong Hyeon Choi South Korea 13 681 1.8× 429 2.4× 225 1.6× 44 0.3× 12 0.1× 33 1.2k
Artur Kowalik Poland 20 519 1.3× 139 0.8× 34 0.2× 472 3.6× 14 0.1× 114 1.6k
Linda G. Rikkert Netherlands 8 375 1.0× 81 0.4× 46 0.3× 47 0.4× 17 0.1× 8 578
Nikesh Kotecha United States 7 564 1.5× 70 0.4× 124 0.9× 191 1.5× 223 1.8× 13 990
Frank Coumans Netherlands 15 421 1.1× 480 2.7× 93 0.7× 694 5.3× 14 0.1× 27 1.3k
Donal P. Hayes Netherlands 6 132 0.3× 64 0.4× 252 1.8× 57 0.4× 46 0.4× 8 566
John Burthem United Kingdom 19 376 1.0× 211 1.2× 25 0.2× 114 0.9× 266 2.1× 51 1.2k
Afroditi Nanou Netherlands 10 258 0.7× 112 0.6× 84 0.6× 150 1.2× 5 0.0× 20 460
Mazen A. Juratli Germany 15 248 0.6× 471 2.6× 75 0.5× 221 1.7× 4 0.0× 47 881

Countries citing papers authored by Ka‐Won Kang

Since Specialization
Citations

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

Fields of papers citing papers by Ka‐Won Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ka‐Won Kang. 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 Ka‐Won Kang. The network helps show where Ka‐Won Kang may publish in the future.

Co-authorship network of co-authors of Ka‐Won Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Ka‐Won Kang. A scholar is included among the top collaborators of Ka‐Won Kang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ka‐Won Kang. Ka‐Won Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Seong, Nak Jong, Ka‐Won Kang, Yong Seek Park, et al.. (2025). Decreased frequency and inflammatory change of FoxP3+ regulatory T cells in immunopathogenesis of human acute graft-versus-host disease. The Korean Journal of Internal Medicine. 40(4). 657–666.
2.
Choi, Yoon Seok, Joonho Shim, Ka‐Won Kang, et al.. (2024). Assessing the Efficacy of Bortezomib and Dexamethasone for Induction and Maintenance Therapy in Relapsed/Refractory Cutaneous T-Cell Lymphoma: A Phase II CISL1701/BIC Study. Cancer Research and Treatment. 57(1). 267–279. 1 indexed citations
3.
Koh, Young‐Il, Ja Min Byun, Junshik Hong, et al.. (2024). Glofitamab combined with poseltinib and lenalidomide for relapsed/refractory diffuse large B cell lymphoma: Interim analysis of GPL study.. Journal of Clinical Oncology. 42(16_suppl). 7066–7066. 2 indexed citations
4.
Jung, Sung‐Hoon, Je‐Jung Lee, Young Rok, et al.. (2024). Comparative analysis of single versus tandem autologous stem cell transplantation in patients with multiple myeloma in Korea: the KMM2102 study. Scientific Reports. 14(1). 24325–24325.
5.
Park, Changhee, Ho Sup Lee, Ka‐Won Kang, et al.. (2024). Combination of acalabrutinib with lenalidomide and rituximab in relapsed/refractory aggressive B-cell non-Hodgkin lymphoma: a single-arm phase II trial. Nature Communications. 15(1). 2776–2776. 6 indexed citations
8.
Shin, Sang-Hoon, Samir Kumar, Dongmin Seo, et al.. (2023). Label-Free CD34+ Cell Identification Using Deep Learning and Lens-Free Shadow Imaging Technology. Biosensors. 13(12). 993–993. 6 indexed citations
10.
Kang, Ka‐Won, Byeong Hyeon Choi, Hyesun Jeong, et al.. (2021). Dual size-exclusion chromatography for efficient isolation of extracellular vesicles from bone marrow derived human plasma. Scientific Reports. 11(1). 217–217. 18 indexed citations
11.
Jeong, Hyesun, Byeong Hyeon Choi, Jik‐Han Jung, et al.. (2021). GCC2 as a New Early Diagnostic Biomarker for Non-Small Cell Lung Cancer. Cancers. 13(21). 5482–5482. 20 indexed citations
12.
Kang, Ka‐Won, Woojune Hur, Hyunku Shin, et al.. (2020). A Proteomic Approach to Understand the Clinical Significance of Acute Myeloid Leukemia–Derived Extracellular Vesicles Reflecting Essential Characteristics of Leukemia. Molecular & Cellular Proteomics. 20. 100017–100017. 12 indexed citations
13.
Park, Yong, Ji Hye Kim, Ka‐Won Kang, et al.. (2020). PD-L1 expression in bone marrow plasma cells as a biomarker to predict multiple myeloma prognosis: developing a nomogram-based prognostic model. Scientific Reports. 10(1). 12641–12641. 29 indexed citations
14.
Shin, Hyunku, Seunghyun Oh, Soonwoo Hong, et al.. (2020). Liquid biopsy of lung cancer by deep learning and spectroscopic analysis of circulating exosomes.. Journal of Clinical Oncology. 38(15_suppl). e15532–e15532. 2 indexed citations
15.
Lee, Seung Jin, et al.. (2019). CXCR2 Ligands and mTOR Activation Enhance Reprogramming of Human Somatic Cells to Pluripotent Stem Cells. Stem Cells and Development. 29(3). 119–132. 13 indexed citations
16.
Kang, Ka‐Won, Se Ryeon Lee, Dae Sik Kim, et al.. (2018). Lack of usefulness of computed tomography for surveillance in patients with aggressive non-Hodgkin lymphoma. PLoS ONE. 13(2). e0192656–e0192656. 1 indexed citations
17.
Lee, Se Ryeon, Ka‐Won Kang, Dae Sik Kim, et al.. (2018). Modified dose of melphalan-prednisone in multiple myeloma patients receiving bortezomib plus melphalan-prednisone treatment. The Korean Journal of Internal Medicine. 34(6). 1333–1346. 1 indexed citations
18.
Byun, Ja Min, et al.. (2017). Clinical Features and Outcomes of Light-Chain Dominant Multiple Myeloma: A Population-Based Study. Blood. 130. 5360. 1 indexed citations
20.
Kim, Dae Sik, Ka‐Won Kang, Se Ryeon Lee, et al.. (2015). Comparison of consolidation strategies in acute myeloid leukemia: high-dose cytarabine alone versus intermediate-dose cytarabine combined with anthracyclines. Annals of Hematology. 94(9). 1485–1492. 13 indexed citations

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026