Hideki Goto
Impact in
- Hematology top 10%
- Hematopoietic Stem Cell Transplantation
-
- CAR-T cell therapy research
Papers in
- Oncology 31
- CAR-T cell therapy research 12
- Polyomavirus and related diseases 5
- Hematology 30
- Hematopoietic Stem Cell Transplantation 23
- Acute Myeloid Leukemia Research 5
- Co-authors
- Takanori Teshima (40 shared papers)Tomoyuki Endo (22 shared papers)Katsuya Fujimoto (11 shared papers)Masahiro Onozawa (20 shared papers)Toshihiko Kobayashi (2 shared papers)Daigo Hashimoto (18 shared papers)Masayuki Yoshida (2 shared papers)Kaoru Kahata (14 shared papers)
- Journals
- International Journal of Hematology (11 papers)Blood (7 papers)International Journal of Clinical Oncology (5 papers)Cytotherapy (3 papers)Biology of Blood and Marrow Transplantation (3 papers)
- Partner nations
- JapanUnited StatesBelgium
In The Last Decade
Hideki Goto
79 papers receiving 580 citations
Peers
Comparison fields: 5 of 107
- Hematology 122
- Oncology 187
- Immunology 126
- Genetics 57
- Transplantation 11
Countries citing papers authored by Hideki Goto
This map shows the geographic impact of Hideki Goto'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 Hideki Goto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideki Goto more than expected).
Fields of papers citing papers by Hideki Goto
This network shows the impact of papers produced by Hideki Goto. 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 Hideki Goto. The network helps show where Hideki Goto may publish in the future.
Co-authors
The 25 scholars most cited alongside Hideki Goto, 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 96 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 51 | |
| 2 | 2007 | 33 | |
| 3 | 2010 | 30 | |
| 4 | 2008 | 26 | |
| 5 | 2017 | 25 | |
| 6 | 1997 | 24 | |
| 7 | 2018 | 24 | |
| 8 | 2019 | 24 | |
| 9 | 2015 | 23 | |
| 10 | 2022 | 21 | |
| 11 | 2019 | 19 | |
| 12 | 2020 | 19 | |
| 13 | 2023 | 16 | |
| 14 | 2003 | 16 | |
| 15 | 2021 | 15 | |
| 16 | 2022 | 12 | |
| 17 | 2023 | 12 | |
| 18 | 2016 | 11 | |
| 19 | 2013 | 11 | |
| 20 | 2018 | 10 |
About Hideki Goto
Hideki Goto is a scholar working on Oncology, Hematology, Molecular Biology, Immunology and Surgery, having authored 96 papers that have together received 597 indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (23 papers), CAR-T cell therapy research (12 papers), Lymphoma Diagnosis and Treatment (11 papers), Chronic Lymphocytic Leukemia Research (8 papers), Acute Lymphoblastic Leukemia research (7 papers), Oral and Maxillofacial Pathology (6 papers), Acute Myeloid Leukemia Research (5 papers) and Polyomavirus and related diseases (5 papers). The work is most often cited by research in Hematology (122 citations), Oncology (187 citations), Immunology (126 citations), Genetics (57 citations) and Transplantation (11 citations). Hideki Goto has collaborated with scholars based in Japan, United States and Belgium. Frequent co-authors include Takanori Teshima, Tomoyuki Endo, Katsuya Fujimoto, Masahiro Onozawa, Toshihiko Kobayashi, Daigo Hashimoto, Masayuki Yoshida, Kaoru Kahata, Keisuke Yamaguchi and Yukari Takeda. Their work appears in journals such as International Journal of Hematology, Blood, International Journal of Clinical Oncology, Cytotherapy and Biology of Blood and Marrow Transplantation.
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.