Jun Kawashima
Impact in
- Genetics top 2%
- Myeloproliferative Neoplasms: Diagnosis and Treatment
- Hemoglobinopathies and Related Disorders
- Hematology top 2%
- Acute Myeloid Leukemia Research
- Chronic Myeloid Leukemia Treatments
Papers in
- Genetics 28
- Myeloproliferative Neoplasms: Diagnosis and Treatment 28
- Hematology 21
- Chronic Myeloid Leukemia Treatments 19
- Co-authors
- Vikas Gupta (24 shared papers)Srđan Verstovšek (19 shared papers)Jean‐Jacques Kiladjian (16 shared papers)Alessandro M. Vannucchi (15 shared papers)David Lavie (12 shared papers)Uwe Platzbecker (11 shared papers)Francesco Passamonti (6 shared papers)Ruben A. Mesa (21 shared papers)
- Journals
- Blood (13 papers)Annals of Surgical Oncology (6 papers)HPB (3 papers)Journal of Clinical Oncology (3 papers)Journal of Surgical Oncology (3 papers)
- Partner nations
- United StatesJapanItaly
In The Last Decade
Jun Kawashima
52 papers receiving 660 citations
Peers
Comparison fields: 5 of 48
- Genetics 522
- Hematology 406
- Rheumatology 164
- Molecular Biology 359
- Oncology 90
Countries citing papers authored by Jun Kawashima
This map shows the geographic impact of Jun Kawashima'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 Jun Kawashima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Kawashima more than expected).
Fields of papers citing papers by Jun Kawashima
This network shows the impact of papers produced by Jun Kawashima. 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 Jun Kawashima. The network helps show where Jun Kawashima may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Kawashima, 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 70 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 212 | |
| 2 | 2020 | 81 | |
| 3 | 2016 | 77 | |
| 4 | 2013 | 35 | |
| 5 | 2023 | 25 | |
| 6 | 2018 | 21 | |
| 7 | 1994 | 18 | |
| 8 | 2022 | 16 | |
| 9 | 2012 | 14 | |
| 10 | 2017 | 14 | |
| 11 | 2017 | 13 | |
| 12 | 2024 | 12 | |
| 13 | 2021 | 12 | |
| 14 | 2023 | 10 | |
| 15 | 2005 | 7 | |
| 16 | 2024 | 6 | |
| 17 | 2022 | 6 | |
| 18 | 2024 | 6 | |
| 19 | 2025 | 5 | |
| 20 | 2022 | 5 |
About Jun Kawashima
Jun Kawashima is a scholar working on Genetics, Hematology, Oncology, Surgery and Pulmonary and Respiratory Medicine, having authored 70 papers that have together received 666 indexed citations. Recurring topics across this work include Myeloproliferative Neoplasms: Diagnosis and Treatment (28 papers), Chronic Myeloid Leukemia Treatments (19 papers), Hepatocellular Carcinoma Treatment and Prognosis (9 papers), Pancreatic and Hepatic Oncology Research (9 papers), Kruppel-like factors research (8 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (8 papers), Gallbladder and Bile Duct Disorders (6 papers) and Gastric Cancer Management and Outcomes (5 papers). The work is most often cited by research in Genetics (522 citations), Hematology (406 citations), Rheumatology (164 citations), Molecular Biology (359 citations) and Oncology (90 citations). Jun Kawashima has collaborated with scholars based in United States, Japan and Italy. Frequent co-authors include Vikas Gupta, Srđan Verstovšek, Jean‐Jacques Kiladjian, Alessandro M. Vannucchi, David Lavie, Uwe Platzbecker, Francesco Passamonti, Ruben A. Mesa, Claire Harrison and Hua Dong. Their work appears in journals such as Blood, Annals of Surgical Oncology, HPB, Journal of Clinical Oncology and Journal of Surgical Oncology.
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.