Sheida Nabavi
Impact in
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Cancer Genomics and Diagnostics 9
- Co-authors
- Tianyu WangClifford YangReda A. AmmarBoyang LiCraig E. NelsonJun BaiAbdelrahman HosnyMohammad Madani
- Journals
- BMC Bioinformatics (7 papers)Medical Physics (2 papers)Bioinformatics (2 papers)BMC Genomics (2 papers)Journal of Cancer Research and Clinical Oncology (2 papers)
- Partner nations
- United StatesIranCanada
In The Last Decade
Sheida Nabavi
47 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 103
- Health Informatics 42
- Radiology, Nuclear Medicine and Imaging 356
- Cancer Research 208
- Artificial Intelligence 424
- Neurology 103
Countries citing papers authored by Sheida Nabavi
This map shows the geographic impact of Sheida Nabavi'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 Sheida Nabavi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheida Nabavi more than expected).
Fields of papers citing papers by Sheida Nabavi
This network shows the impact of papers produced by Sheida Nabavi. 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 Sheida Nabavi. The network helps show where Sheida Nabavi may publish in the future.
Co-authors
The 25 scholars most cited alongside Sheida Nabavi, 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 | 0 | |
| 2 | 2024 | 27 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 4 | |
| 6 | 2022 | 1 | |
| 7 | 2021 | 104 | |
| 8 | 2020 | 23 | |
| 9 | 2020 | 43 | |
| 10 | 2019 | 179 | |
| 11 | 2019 | 4 | |
| 12 | 2019 | 181 | |
| 13 | 2018 | 1 | |
| 14 | 2018 | 3 | |
| 15 | 2018 | 6 | |
| 16 | 2018 | 30 | |
| 17 | 2016 | 59 | |
| 18 | 2016 | 6 | |
| 19 | 2014 | 49 | |
| 20 | 2013 | 8 |
About Sheida Nabavi
Sheida Nabavi is a scholar working on Cancer Research, Health Informatics, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Genetics, having authored 50 papers that have together received 1.1k indexed citations. Recurring topics across this work include AI in cancer detection (16 papers), Radiomics and Machine Learning in Medical Imaging (13 papers), Gene expression and cancer classification (13 papers), Genomic variations and chromosomal abnormalities (11 papers), Single-cell and spatial transcriptomics (9 papers), Cancer Genomics and Diagnostics (9 papers), Bioinformatics and Genomic Networks (7 papers) and COVID-19 diagnosis using AI (6 papers). The work is most often cited by research in Health Informatics (42 citations), Radiology, Nuclear Medicine and Imaging (356 citations), Cancer Research (208 citations), Artificial Intelligence (424 citations) and Neurology (103 citations). Sheida Nabavi has collaborated with scholars based in United States, Iran and Canada. Frequent co-authors include Tianyu Wang, Clifford Yang, Reda A. Ammar, Boyang Li, Craig E. Nelson, Jun Bai, Abdelrahman Hosny, Mohammad Madani, Michelle T. Dow and Jinbo Bi. Their work appears in journals such as BMC Bioinformatics, Medical Physics, Bioinformatics, BMC Genomics and Journal of Cancer Research and Clinical Oncology.
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.