Tokiya Abe
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
- Hepatology top 10%
- Hepatocellular Carcinoma Treatment and Prognosis
Papers in
-
- Digital Imaging for Blood Diseases 17
- Image Retrieval and Classification Techniques 7
- Medical Image Segmentation Techniques 5
-
- AI in cancer detection 25
- Co-authors
- Michiie Sakamoto (29 shared papers)Masahiro Yamaguchi (26 shared papers)Akinori Hashiguchi (25 shared papers)Nagaaki Ohyama (10 shared papers)Yukako Yagi (10 shared papers)Yohei Masugi (6 shared papers)Yuri Murakami (13 shared papers)Pinky A. Bautista (8 shared papers)
- Journals
- Pathology International (2 papers)Computerized Medical Imaging and Graphics (2 papers)Hepatology Research (2 papers)Analytical Cellular Pathology (2 papers)Journal of Pathology Informatics (2 papers)
- Partner nations
- JapanUnited StatesRussia
In The Last Decade
Tokiya Abe
49 papers receiving 627 citations
Peers
Comparison fields: 5 of 84
- Biophysics 96
- Hepatology 115
- Computer Vision and Pattern Recognition 150
- Oncology 176
- Artificial Intelligence 166
Countries citing papers authored by Tokiya Abe
This map shows the geographic impact of Tokiya Abe'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 Tokiya Abe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tokiya Abe more than expected).
Fields of papers citing papers by Tokiya Abe
This network shows the impact of papers produced by Tokiya Abe. 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 Tokiya Abe. The network helps show where Tokiya Abe may publish in the future.
Co-authors
The 25 scholars most cited alongside Tokiya Abe, 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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 73 | |
| 2 | 2020 | 72 | |
| 3 | 2017 | 46 | |
| 4 | 2016 | 38 | |
| 5 | 2013 | 33 | |
| 6 | 2008 | 30 | |
| 7 | 2012 | 28 | |
| 8 | 2005 | 28 | |
| 9 | 2005 | 26 | |
| 10 | 2005 | 24 | |
| 11 | 2014 | 23 | |
| 12 | 2013 | 22 | |
| 13 | 2018 | 22 | |
| 14 | 2018 | 22 | |
| 15 | 1996 | 18 | |
| 16 | 2012 | 13 | |
| 17 | 2019 | 13 | |
| 18 | 2016 | 10 | |
| 19 | 2015 | 9 | |
| 20 | 2016 | 9 |
About Tokiya Abe
Tokiya Abe is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Oncology, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 49 papers that have together received 645 indexed citations. Recurring topics across this work include AI in cancer detection (25 papers), Digital Imaging for Blood Diseases (17 papers), Image Retrieval and Classification Techniques (7 papers), Cell Image Analysis Techniques (6 papers), Pancreatic and Hepatic Oncology Research (6 papers), Medical Image Segmentation Techniques (5 papers), Liver Disease Diagnosis and Treatment (5 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). The work is most often cited by research in Biophysics (96 citations), Hepatology (115 citations), Computer Vision and Pattern Recognition (150 citations), Oncology (176 citations) and Artificial Intelligence (166 citations). Tokiya Abe has collaborated with scholars based in Japan, United States and Russia. Frequent co-authors include Michiie Sakamoto, Masahiro Yamaguchi, Akinori Hashiguchi, Nagaaki Ohyama, Yukako Yagi, Yohei Masugi, Yuri Murakami, Pinky A. Bautista, Minoru Kitago and Akihisa Ueno. Their work appears in journals such as Pathology International, Computerized Medical Imaging and Graphics, Hepatology Research, Analytical Cellular Pathology and Journal of Pathology Informatics.
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.