Mi Kwon
Impact in
- Hematology top 1%
- Hematopoietic Stem Cell Transplantation
- Acute Myeloid Leukemia Research
- Oncology top 2%
- CAR-T cell therapy research
- COVID-19 and healthcare impacts
Papers in
- Hematology 92
- Hematopoietic Stem Cell Transplantation 79
- Acute Myeloid Leukemia Research 13
- Oncology 53
- CAR-T cell therapy research 42
- COVID-19 and healthcare impacts 6
- Co-authors
- José Luis Díez-Martín (76 shared papers)Ismael Buño (48 shared papers)Javier Anguita (44 shared papers)Carolina Martínez‐Laperche (37 shared papers)Pascual Balsalobre (31 shared papers)David Serrano (34 shared papers)Rebeca Bailén (36 shared papers)Jorge Gayoso (30 shared papers)
In The Last Decade
Mi Kwon
155 papers receiving 2.9k citations
Mi Kwon's Hit Papers
Peers
Comparison fields: 5 of 81
- Hematology 1k
- Oncology 1.1k
- Virology 121
- Infectious Diseases 397
- Pathology and Forensic Medicine 248
Countries citing papers authored by Mi Kwon
This map shows the geographic impact of Mi Kwon'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 Mi Kwon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mi Kwon more than expected).
Fields of papers citing papers by Mi Kwon
This network shows the impact of papers produced by Mi Kwon. 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 Mi Kwon. The network helps show where Mi Kwon may publish in the future.
Co-authors
The 25 scholars most cited alongside Mi Kwon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 165 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 179 | |
| 2 | 2021 | 177 | |
| 3 | 2020 | 122 | |
| 4 | 2023 | 118 | |
| 5 | 2021 | 117 | |
| 6 | 2022 | 106 | |
| 7 | 2023 | 100 | |
| 8 | 2021 | 96 | |
| 9 | Axatilimab in Recurrent or Refractory Chronic Graft-versus-Host Disease Hit paper breakdown → | 2024 | 93 |
| 10 | 2011 | 92 | |
| 11 | 2022 | 67 | |
| 12 | 2012 | 64 | |
| 13 | 2014 | 63 | |
| 14 | 2021 | 62 | |
| 15 | 2018 | 51 | |
| 16 | 2018 | 49 | |
| 17 | 2024 | 44 | |
| 18 | 2014 | 40 | |
| 19 | 2021 | 37 | |
| 20 | 2019 | 35 |
About Mi Kwon
Mi Kwon is a scholar working on Hematology, Oncology, Virology, Infectious Diseases and Pathology and Forensic Medicine, having authored 165 papers that have together received 2.9k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (79 papers), CAR-T cell therapy research (42 papers), Acute Myeloid Leukemia Research (13 papers), HIV Research and Treatment (10 papers), COVID-19 Clinical Research Studies (8 papers), Antifungal resistance and susceptibility (7 papers), COVID-19 and healthcare impacts (6 papers) and Lymphoma Diagnosis and Treatment (6 papers). The work is most often cited by research in Hematology (1k citations), Oncology (1.1k citations), Virology (121 citations), Infectious Diseases (397 citations) and Pathology and Forensic Medicine (248 citations). Mi Kwon has collaborated with scholars based in Spain, France and Germany. Frequent co-authors include José Luis Díez-Martín, Ismael Buño, Javier Anguita, Carolina Martínez‐Laperche, Pascual Balsalobre, David Serrano, Rebeca Bailén, Jorge Gayoso, Ana Maria Pérez‐Corral and Nieves Dorado. Their work appears in journals such as Blood, Transplantation and Cellular Therapy, Bone Marrow Transplantation, Frontiers in Immunology and Leukemia.
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.