Simukayi Mutasa
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- COVID-19 diagnosis using AI
Papers in
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- Radiomics and Machine Learning in Medical Imaging 12
- MRI in cancer diagnosis 4
-
- AI in cancer detection 11
- Co-authors
- Richard Ha (19 shared papers)Peter Chang (13 shared papers)Sachin Jambawalikar (15 shared papers)Shawn Sun (3 shared papers)Michael Z. Liu (12 shared papers)Jenika Karcich (9 shared papers)Eduardo Pascual Van Sant (7 shared papers)Carrie Ruzal‐Shapiro (2 shared papers)
- Journals
- Journal of Digital Imaging (7 papers)American Journal of Roentgenology (3 papers)Stroke (3 papers)Clinical Breast Cancer (2 papers)Breast Cancer Research and Treatment (2 papers)
- Partner nations
- United States
In The Last Decade
Simukayi Mutasa
38 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 119
- Health Informatics 168
- Radiology, Nuclear Medicine and Imaging 549
- Artificial Intelligence 383
- Oral Surgery 44
- Health Information Management 27
Countries citing papers authored by Simukayi Mutasa
This map shows the geographic impact of Simukayi Mutasa'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 Simukayi Mutasa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simukayi Mutasa more than expected).
Fields of papers citing papers by Simukayi Mutasa
This network shows the impact of papers produced by Simukayi Mutasa. 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 Simukayi Mutasa. The network helps show where Simukayi Mutasa may publish in the future.
Co-authors
The 25 scholars most cited alongside Simukayi Mutasa, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 167 | |
| 2 | 2018 | 98 | |
| 3 | 2019 | 95 | |
| 4 | 2020 | 78 | |
| 5 | 2018 | 70 | |
| 6 | 2019 | 62 | |
| 7 | 2018 | 57 | |
| 8 | 2018 | 53 | |
| 9 | 2019 | 51 | |
| 10 | 2019 | 50 | |
| 11 | 2018 | 44 | |
| 12 | 2022 | 40 | |
| 13 | 2020 | 37 | |
| 14 | 2018 | 35 | |
| 15 | 2020 | 32 | |
| 16 | 2020 | 26 | |
| 17 | 2021 | 26 | |
| 18 | 2018 | 26 | |
| 19 | 2020 | 25 | |
| 20 | 2018 | 19 |
About Simukayi Mutasa
Simukayi Mutasa is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Health Informatics, Biomedical Engineering and Surgery, having authored 38 papers that have together received 1.2k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), AI in cancer detection (11 papers), Artificial Intelligence in Healthcare and Education (8 papers), MRI in cancer diagnosis (4 papers), Medical Imaging and Analysis (4 papers), Advanced X-ray and CT Imaging (3 papers), Breast Cancer Treatment Studies (3 papers) and Intracerebral and Subarachnoid Hemorrhage Research (3 papers). The work is most often cited by research in Health Informatics (168 citations), Radiology, Nuclear Medicine and Imaging (549 citations), Artificial Intelligence (383 citations), Oral Surgery (44 citations) and Health Information Management (27 citations). Simukayi Mutasa has collaborated with scholars based in United States. Frequent co-authors include Richard Ha, Peter Chang, Sachin Jambawalikar, Shawn Sun, Michael Z. Liu, Jenika Karcich, Eduardo Pascual Van Sant, Carrie Ruzal‐Shapiro, Ralph Wynn and Rama S. Ayyala. Their work appears in journals such as Journal of Digital Imaging, American Journal of Roentgenology, Stroke, Clinical Breast Cancer and Breast Cancer Research and Treatment.
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.