Felipe Kitamura
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Autopsy Techniques and Outcomes
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 19
- COVID-19 diagnosis using AI 7
- Radiology practices and education 5
- Autopsy Techniques and Outcomes 3
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- Artificial Intelligence in Healthcare and Education 23
- Co-authors
- Bradley J. Erickson (5 shared papers)Ian Pan (7 shared papers)Nitamar Abdala (8 shared papers)Luciano M. Prevedello (6 shared papers)Katherine P. Andriole (5 shared papers)Jayashree Kalpathy–Cramer (4 shared papers)Adam E. Flanders (5 shared papers)George Shih (4 shared papers)
- Journals
- Radiology Artificial Intelligence (11 papers)Radiology (5 papers)Journal of Digital Imaging (2 papers)European Radiology (2 papers)Stroke (2 papers)
- Partner nations
- BrazilUnited StatesCanada
In The Last Decade
Felipe Kitamura
40 papers receiving 953 citations
Peers
Comparison fields: 5 of 132
- Health Informatics 265
- Radiology, Nuclear Medicine and Imaging 334
- Archeology 135
- Oral Surgery 67
- Health Information Management 30
Countries citing papers authored by Felipe Kitamura
This map shows the geographic impact of Felipe Kitamura'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 Felipe Kitamura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felipe Kitamura more than expected).
Fields of papers citing papers by Felipe Kitamura
This network shows the impact of papers produced by Felipe Kitamura. 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 Felipe Kitamura. The network helps show where Felipe Kitamura may publish in the future.
Co-authors
The 25 scholars most cited alongside Felipe Kitamura, 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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 315 | |
| 2 | 2021 | 197 | |
| 3 | 2020 | 69 | |
| 4 | 2022 | 53 | |
| 5 | 2023 | 51 | |
| 6 | 2023 | 31 | |
| 7 | 2020 | 23 | |
| 8 | 2021 | 18 | |
| 9 | 2021 | 18 | |
| 10 | 2019 | 18 | |
| 11 | 2023 | 16 | |
| 12 | 2023 | 16 | |
| 13 | 2021 | 14 | |
| 14 | 2024 | 14 | |
| 15 | 2024 | 14 | |
| 16 | 2021 | 13 | |
| 17 | 2020 | 11 | |
| 18 | 2022 | 10 | |
| 19 | 2024 | 8 | |
| 20 | 2024 | 8 |
About Felipe Kitamura
Felipe Kitamura is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics, Artificial Intelligence, Biomedical Engineering and Pulmonary and Respiratory Medicine, having authored 46 papers that have together received 975 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (23 papers), Radiomics and Machine Learning in Medical Imaging (19 papers), COVID-19 diagnosis using AI (7 papers), AI in cancer detection (7 papers), Radiology practices and education (5 papers), Medical Imaging and Analysis (4 papers), Autopsy Techniques and Outcomes (3 papers) and Intracerebral and Subarachnoid Hemorrhage Research (3 papers). The work is most often cited by research in Health Informatics (265 citations), Radiology, Nuclear Medicine and Imaging (334 citations), Archeology (135 citations), Oral Surgery (67 citations) and Health Information Management (30 citations). Felipe Kitamura has collaborated with scholars based in Brazil, United States and Canada. Frequent co-authors include Bradley J. Erickson, Ian Pan, Nitamar Abdala, Luciano M. Prevedello, Katherine P. Andriole, Jayashree Kalpathy–Cramer, Adam E. Flanders, George Shih, Alexander Bilbily and Artem B. Mamonov. Their work appears in journals such as Radiology Artificial Intelligence, Radiology, Journal of Digital Imaging, European Radiology and Stroke.
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.