Takashi Kumada
- Hepatology top 0.05%
- Epidemiology top 0.1%
- Surgery top 1%
- Cancer Research top 0.5%
- Oncology top 1%
- Co-authors
- Hidenori ToyodaToshifumi TadaSeiki KiriyamaYasuhiro SoneMasatoshi KudoYuji KaneokaShinji SatomuraPhilip J. Johnson
- Topics
- Liver Disease Diagnosis and Treatment (237 papers)Hepatitis C virus research (174 papers)Hepatocellular Carcinoma Treatment and Prognosis (151 papers)
- Journals
- Journal of Biological ChemistryJournal of Clinical OncologySHILAP Revista de lepidopterología
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Takashi Kumada
378 papers receiving 11.5k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Hepatology 8.6k
- Epidemiology 6.9k
- Surgery 2.0k
- Cancer Research 1.7k
- Oncology 1.7k
Countries citing papers authored by Takashi Kumada
This map shows the geographic impact of Takashi Kumada'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 Takashi Kumada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takashi Kumada more than expected).
Fields of papers citing papers by Takashi Kumada
This network shows the impact of papers produced by Takashi Kumada. 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 Takashi Kumada. The network helps show where Takashi Kumada may publish in the future.
Co-authorship network of co-authors of Takashi Kumada
This figure shows the co-authorship network connecting the top 25 collaborators of Takashi Kumada. A scholar is included among the top collaborators of Takashi Kumada 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 Takashi Kumada. Takashi Kumada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 2 | |
| 5 | 8 | |
| 6 | 6 | |
| 7 | 5 | |
| 8 | 8 | |
| 9 | 6 | |
| 10 | 0 | |
| 11 | 8 | |
| 12 | 36 | |
| 13 | 25 | |
| 14 | 12 | |
| 15 | 27 | |
| 16 | 81 | |
| 17 | Development of pre and post-operative models to predict early recurrence of hepatocellular carcinoma after surgical resectionbreakdown → | 349 |
| 18 | 77 | |
| 19 | 7 | |
| 20 | 8 |
About Takashi Kumada
Takashi Kumada is a scholar working on Hepatology, Epidemiology and Cancer Research, having authored 399 papers that have together received 11.7k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (237 papers), Hepatitis C virus research (174 papers) and Hepatocellular Carcinoma Treatment and Prognosis (151 papers). The work is most often cited by research in Hepatology (8.6k citations), Epidemiology (6.9k citations) and Cancer Research (1.7k citations). Takashi Kumada has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Hidenori Toyoda, Toshifumi Tada, Seiki Kiriyama, Yasuhiro Sone, Masatoshi Kudo, Yuji Kaneoka, Shinji Satomura, Philip J. Johnson, Junko Tanaka and Sarah Berhane. Their work appears in journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.