Koji Arihiro
Impact in
- Oncology top 1%
- Colorectal Cancer Screening and Detection
- Cancer Immunotherapy and Biomarkers
- Hepatology top 2%
Papers in
- Co-authors
- Kazuaki Chayama (98 shared papers)Kazuaki Tanabe (12 shared papers)Shinji Tanaka (64 shared papers)Ryungsa Kim (15 shared papers)Manabu Emi (5 shared papers)Shiro Oka (48 shared papers)Kouki Inai (19 shared papers)Hideki Ohdan (36 shared papers)
- Journals
- Hepatology Research (10 papers)Gastrointestinal Endoscopy (9 papers)Breast Cancer (9 papers)PLoS ONE (8 papers)Journal of Gastroenterology and Hepatology (8 papers)
- Partner nations
- JapanUnited StatesVietnam
In The Last Decade
Koji Arihiro
324 papers receiving 6.7k citations
Koji Arihiro's Hit Papers
Peers
Comparison fields: 5 of 143
- Oncology 1.6k
- Hepatology 448
- Pulmonary and Respiratory Medicine 1.2k
- Immunology 816
- Gastroenterology 197
Countries citing papers authored by Koji Arihiro
This map shows the geographic impact of Koji Arihiro'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 Koji Arihiro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Koji Arihiro more than expected).
Fields of papers citing papers by Koji Arihiro
This network shows the impact of papers produced by Koji Arihiro. 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 Koji Arihiro. The network helps show where Koji Arihiro may publish in the future.
Co-authors
The 25 scholars most cited alongside Koji Arihiro, 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 357 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 362 | |
| 2 | Deep Learning Models for Histopathological Classification of Gastric and Colonic Epithelial Tumours Hit paper breakdown → | 2020 | 273 |
| 3 | 2008 | 177 | |
| 4 | 2014 | 159 | |
| 5 | 2007 | 159 | |
| 6 | 2006 | 155 | |
| 7 | 2011 | 145 | |
| 8 | 2010 | 138 | |
| 9 | 2008 | 126 | |
| 10 | 2010 | 111 | |
| 11 | 2005 | 110 | |
| 12 | 2015 | 101 | |
| 13 | 2016 | 99 | |
| 14 | 2007 | 89 | |
| 15 | 2017 | 89 | |
| 16 | 2008 | 86 | |
| 17 | 2000 | 83 | |
| 18 | 2015 | 81 | |
| 19 | 2005 | 73 | |
| 20 | 2009 | 65 |
About Koji Arihiro
Koji Arihiro is a scholar working on Oncology, Surgery, Pulmonary and Respiratory Medicine, Molecular Biology and Cancer Research, having authored 357 papers that have together received 6.8k indexed citations. Recurring topics across this work include Gastric Cancer Management and Outcomes (29 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (22 papers), Pancreatic and Hepatic Oncology Research (21 papers), Breast Cancer Treatment Studies (16 papers), Metastasis and carcinoma case studies (15 papers), Esophageal Cancer Research and Treatment (14 papers), Liver Disease Diagnosis and Treatment (14 papers) and Sarcoma Diagnosis and Treatment (13 papers). The work is most often cited by research in Oncology (1.6k citations), Hepatology (448 citations), Pulmonary and Respiratory Medicine (1.2k citations), Immunology (816 citations) and Gastroenterology (197 citations). Koji Arihiro has collaborated with scholars based in Japan, United States and Vietnam. Frequent co-authors include Kazuaki Chayama, Kazuaki Tanabe, Shinji Tanaka, Ryungsa Kim, Manabu Emi, Shiro Oka, Kouki Inai, Hideki Ohdan, Hideyuki Hyogo and Takayuki Kadoya. Their work appears in journals such as Hepatology Research, Gastrointestinal Endoscopy, Breast Cancer, PLoS ONE and Journal of Gastroenterology and Hepatology.
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.