Hideki Maeda
Impact in
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
- Clinical Biochemistry top 10%
Papers in ⓘ
-
- Statistical Methods in Clinical Trials 7
- Co-authors
- Goro Kutomi (9 shared papers)Mitsuru Mori (5 shared papers)Haruo UZAWA (3 shared papers)Toshihiko Torigoe (3 shared papers)Kaori Takai (1 shared paper)Hiroeki Sahara (2 shared papers)Hiroto Ikeda (1 shared paper)Kenji Okita (1 shared paper)
- Journals
- Frontiers in Medicine (4 papers)Biological and Pharmaceutical Bulletin (3 papers)Clinical Pharmacology & Therapeutics (3 papers)International Journal of Clinical Oncology (3 papers)Japanese Journal of Clinical Oncology (3 papers)
- Partner nations
- JapanUnited StatesGermany
In The Last Decade
Hideki Maeda
90 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 131
- Cancer Research 213
- Clinical Biochemistry 55
- Molecular Biology 490
- Biophysics 30
- Economics and Econometrics 133
Countries citing papers authored by Hideki Maeda
This map shows the geographic impact of Hideki Maeda'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 Maeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideki Maeda more than expected).
Fields of papers citing papers by Hideki Maeda
This network shows the impact of papers produced by Hideki Maeda. 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 Maeda. The network helps show where Hideki Maeda may publish in the future.
Co-authors
The 25 scholars most cited alongside Hideki Maeda, 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 102 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 210 | |
| 2 | 1997 | 63 | |
| 3 | 1985 | 57 | |
| 4 | 2020 | 47 | |
| 5 | 2015 | 43 | |
| 6 | 1987 | 40 | |
| 7 | 1991 | 39 | |
| 8 | 1983 | 38 | |
| 9 | 1992 | 38 | |
| 10 | 1993 | 30 | |
| 11 | 2012 | 28 | |
| 12 | 2002 | 26 | |
| 13 | 2020 | 22 | |
| 14 | 2015 | 21 | |
| 15 | 2017 | 19 | |
| 16 | 1998 | 17 | |
| 17 | 2014 | 16 | |
| 18 | 2014 | 15 | |
| 19 | 1999 | 15 | |
| 20 | 2001 | 11 |
About Hideki Maeda
Hideki Maeda is a scholar working on Toxicology, Statistics and Probability, Economics and Econometrics, Cancer Research and Oncology, having authored 102 papers that have together received 1.1k indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (21 papers), Pharmaceutical Economics and Policy (14 papers), Cancer Treatment and Pharmacology (7 papers), Statistical Methods in Clinical Trials (7 papers), Prostate Cancer Treatment and Research (6 papers), Biomedical Ethics and Regulation (6 papers), Economic and Financial Impacts of Cancer (5 papers) and Chronic Lymphocytic Leukemia Research (5 papers). The work is most often cited by research in Cancer Research (213 citations), Clinical Biochemistry (55 citations), Molecular Biology (490 citations), Biophysics (30 citations) and Economics and Econometrics (133 citations). Hideki Maeda has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Goro Kutomi, Mitsuru Mori, Haruo UZAWA, Toshihiko Torigoe, Kaori Takai, Hiroeki Sahara, Hiroto Ikeda, Kenji Okita, Atsushi Tanabe and K Takata. Their work appears in journals such as Frontiers in Medicine, Biological and Pharmaceutical Bulletin, Clinical Pharmacology & Therapeutics, International Journal of Clinical Oncology and Japanese Journal of Clinical 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.