Fabíola Macruz
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
Papers in
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- Advanced Neuroimaging Techniques and Applications 2
- Radiomics and Machine Learning in Medical Imaging 2
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- Traumatic Brain Injury Research 3
- Acute Ischemic Stroke Management 2
- Co-authors
- Greg Zaharchuk (1 shared paper)Athanasia Boumis (1 shared paper)Mehdi Khalighi (1 shared paper)Sharon J. Sha (1 shared paper)Kathleen L. Poston (1 shared paper)Michael D. Greicius (1 shared paper)Kevin T. Chen (1 shared paper)Enhao Gong (1 shared paper)
- Journals
- Radiology Artificial Intelligence (2 papers)Scientific Reports (1 paper)Radiology (1 paper)Neurological Sciences (1 paper)Brain and Behavior (1 paper)
- Partner nations
- United StatesBrazilItaly
In The Last Decade
Fabíola Macruz
10 papers receiving 292 citations
Peers
Comparison fields: 5 of 50
- Health Informatics 19
- Radiology, Nuclear Medicine and Imaging 211
- Radiation 36
- Neurology 22
- Neurology 33
Countries citing papers authored by Fabíola Macruz
This map shows the geographic impact of Fabíola Macruz'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 Fabíola Macruz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabíola Macruz more than expected).
Fields of papers citing papers by Fabíola Macruz
This network shows the impact of papers produced by Fabíola Macruz. 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 Fabíola Macruz. The network helps show where Fabíola Macruz may publish in the future.
Co-authors
The 25 scholars most cited alongside Fabíola Macruz, 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 | 2018 | 182 | |
| 2 | 2020 | 23 | |
| 3 | 2018 | 18 | |
| 4 | 2021 | 16 | |
| 5 | 2022 | 16 | |
| 6 | 2023 | 13 | |
| 7 | 2022 | 12 | |
| 8 | 2022 | 10 | |
| 9 | 2021 | 3 | |
| 10 | 2021 | 1 | |
| 11 | 2024 | 0 |
About Fabíola Macruz
Fabíola Macruz is a scholar working on Radiology, Nuclear Medicine and Imaging, Epidemiology, Neurology, Biomedical Engineering and Pulmonary and Respiratory Medicine, having authored 11 papers that have together received 294 indexed citations. Recurring topics across this work include Traumatic Brain Injury and Neurovascular Disturbances (3 papers), Traumatic Brain Injury Research (3 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Acute Ischemic Stroke Management (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Imaging and Analysis (2 papers) and Electrical and Bioimpedance Tomography (1 paper). The work is most often cited by research in Health Informatics (19 citations), Radiology, Nuclear Medicine and Imaging (211 citations), Radiation (36 citations), Neurology (22 citations) and Neurology (33 citations). Fabíola Macruz has collaborated with scholars based in United States, Brazil and Italy. Frequent co-authors include Greg Zaharchuk, Athanasia Boumis, Mehdi Khalighi, Sharon J. Sha, Kathleen L. Poston, Michael D. Greicius, Kevin T. Chen, Enhao Gong, John M. Pauly and Junshen Xu. Their work appears in journals such as Radiology Artificial Intelligence, Scientific Reports, Radiology, Neurological Sciences and Brain and Behavior.
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.