Dai Chihara
Impact in
- Pathology and Forensic Medicine top 0.5%
- Lymphoma Diagnosis and Treatment
- Genetics top 1%
- Chronic Lymphocytic Leukemia Research
Papers in
-
- Lymphoma Diagnosis and Treatment 83
- Oncology 44
- Viral-associated cancers and disorders 24
- CAR-T cell therapy research 15
- Co-authors
- Keitaro Matsuo (11 shared papers)Hidemi Ito (10 shared papers)Tomohiro Matsuda (7 shared papers)Yasuhiro Oki (28 shared papers)Loretta J. Nastoupil (32 shared papers)Akiko Shibata (5 shared papers)Tomotaka Sobue (5 shared papers)Nathan Fowler (17 shared papers)
- Journals
- Blood (37 papers)British Journal of Haematology (7 papers)Blood Advances (6 papers)Annals of Oncology (5 papers)Hematological Oncology (4 papers)
- Partner nations
- United StatesJapanAustralia
In The Last Decade
Dai Chihara
125 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 85
- Pathology and Forensic Medicine 1.1k
- Genetics 608
- Hematology 336
- Oncology 754
- Neurology 315
Countries citing papers authored by Dai Chihara
This map shows the geographic impact of Dai Chihara'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 Dai Chihara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dai Chihara more than expected).
Fields of papers citing papers by Dai Chihara
This network shows the impact of papers produced by Dai Chihara. 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 Dai Chihara. The network helps show where Dai Chihara may publish in the future.
Co-authors
The 25 scholars most cited alongside Dai Chihara, 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 133 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 228 | |
| 2 | 2014 | 126 | |
| 3 | 2015 | 124 | |
| 4 | 2012 | 95 | |
| 5 | 2016 | 86 | |
| 6 | 2011 | 75 | |
| 7 | 2016 | 74 | |
| 8 | 2015 | 74 | |
| 9 | 2015 | 72 | |
| 10 | 2020 | 64 | |
| 11 | 2015 | 62 | |
| 12 | 2016 | 57 | |
| 13 | 2023 | 54 | |
| 14 | 2014 | 37 | |
| 15 | 2015 | 36 | |
| 16 | 2022 | 35 | |
| 17 | 2012 | 34 | |
| 18 | 2014 | 34 | |
| 19 | 2012 | 33 | |
| 20 | 2014 | 32 |
About Dai Chihara
Dai Chihara is a scholar working on Pathology and Forensic Medicine, Oncology, Genetics, Immunology and Neurology, having authored 133 papers that have together received 2.3k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (83 papers), Chronic Lymphocytic Leukemia Research (27 papers), Viral-associated cancers and disorders (24 papers), CNS Lymphoma Diagnosis and Treatment (22 papers), T-cell and Retrovirus Studies (18 papers), CAR-T cell therapy research (15 papers), Acute Lymphoblastic Leukemia research (10 papers) and Chronic Myeloid Leukemia Treatments (6 papers). The work is most often cited by research in Pathology and Forensic Medicine (1.1k citations), Genetics (608 citations), Hematology (336 citations), Oncology (754 citations) and Neurology (315 citations). Dai Chihara has collaborated with scholars based in United States, Japan and Australia. Frequent co-authors include Keitaro Matsuo, Hidemi Ito, Tomohiro Matsuda, Yasuhiro Oki, Loretta J. Nastoupil, Akiko Shibata, Tomotaka Sobue, Nathan Fowler, Shigeo Nakamura and Lindsay M. Morton. Their work appears in journals such as Blood, British Journal of Haematology, Blood Advances, Annals of Oncology and Hematological 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.