Takeshi Yokoo
- Hepatology top 0.5%
- Hepatocellular Carcinoma Treatment and Prognosis 23
- Liver Disease and Transplantation 11
- Epidemiology top 0.5%
- Liver Disease Diagnosis and Treatment 41
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- Advanced MRI Techniques and Applications 28
- MRI in cancer diagnosis 27
- Radiomics and Machine Learning in Medical Imaging 6
- Genetics top 5%
- Hemoglobinopathies and Related Disorders 7
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- Renal cell carcinoma treatment 5
- Co-authors
- Claude B. SirlinMichael S. MiddletonGavin HamiltonMark BydderJeffrey B. SchwimmerJoel E. LavineAlyssa ChavezMichael E. Schroeder
- Journals
- Journal of Magnetic Resonance Imaging (9 papers)Radiology (8 papers)Abdominal Radiology (5 papers)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Takeshi Yokoo
70 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Hepatology 1.6k
- Epidemiology 2.6k
- Radiology, Nuclear Medicine and Imaging 1.7k
- Endocrinology, Diabetes and Metabolism 493
- Genetics 214
Countries citing papers authored by Takeshi Yokoo
This map shows the geographic impact of Takeshi Yokoo'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 Takeshi Yokoo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takeshi Yokoo more than expected).
Fields of papers citing papers by Takeshi Yokoo
This network shows the impact of papers produced by Takeshi Yokoo. 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 Takeshi Yokoo. The network helps show where Takeshi Yokoo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Takeshi Yokoo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 3 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 64 | |
| 5 | 2023 | 41 | |
| 6 | 2021 | 42 | |
| 7 | 2020 | 105 | |
| 8 | 2020 | 22 | |
| 9 | 2020 | 60 | |
| 10 | 2020 | 17 | |
| 11 | 2019 | 31 | |
| 12 | 2018 | 124 | |
| 13 | 2016 | 56 | |
| 14 | 2016 | 2 | |
| 15 | 2011 | 1 | |
| 16 | 2010 | 12 | |
| 17 | 2010 | 41 | |
| 18 | In vivo characterization of the liver fat 1H MR spectrumbreakdown → | 2010 | 429 |
| 19 | 2008 | 20 | |
| 20 | 2001 | 60 |
About Takeshi Yokoo
Takeshi Yokoo is a scholar working on Hepatology, Radiology, Nuclear Medicine and Imaging and Epidemiology, having authored 74 papers that have together received 4.3k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (41 papers), Advanced MRI Techniques and Applications (28 papers), MRI in cancer diagnosis (27 papers), Hepatocellular Carcinoma Treatment and Prognosis (23 papers), Liver Disease and Transplantation (11 papers), Hemoglobinopathies and Related Disorders (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Renal cell carcinoma treatment (5 papers). The work is most often cited by research in Hepatology (1.6k citations), Epidemiology (2.6k citations) and Radiology, Nuclear Medicine and Imaging (1.7k citations). Takeshi Yokoo has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Claude B. Sirlin, Michael S. Middleton, Gavin Hamilton, Mark Bydder, Jeffrey B. Schwimmer, Joel E. Lavine, Alyssa Chavez, Michael E. Schroeder, Irene Cruite and Heather Patton. Their work appears in journals such as Journal of Magnetic Resonance Imaging, Radiology, Abdominal Radiology, Magnetic Resonance in Medicine and Magnetic Resonance Imaging.
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.