Mohammad Peikari
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- AI in cancer detection 7
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- Digital Imaging for Blood Diseases 4
- Co-authors
- Anne L. Martel (7 shared papers)Sherine Salama (5 shared papers)Sharon Nofech‐Mozes (5 shared papers)Mehrdad J. Gangeh (2 shared papers)Judit Zubovits (1 shared paper)G. Clarke (1 shared paper)Shazia Akbar (2 shared papers)Gábor Fichtinger (3 shared papers)
- Journals
- Scientific Reports (2 papers)Medical Physics (1 paper)IEEE Transactions on Medical Imaging (1 paper)PLoS ONE (1 paper)European Heart Journal (1 paper)
- Partner nations
- CanadaUnited States
In The Last Decade
Mohammad Peikari
12 papers receiving 274 citations
Peers
Comparison fields: 5 of 77
- Biophysics 42
- Radiology, Nuclear Medicine and Imaging 112
- Artificial Intelligence 170
- Health Informatics 6
- Computer Vision and Pattern Recognition 87
Countries citing papers authored by Mohammad Peikari
This map shows the geographic impact of Mohammad Peikari'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 Mohammad Peikari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Peikari more than expected).
Fields of papers citing papers by Mohammad Peikari
This network shows the impact of papers produced by Mohammad Peikari. 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 Mohammad Peikari. The network helps show where Mohammad Peikari may publish in the future.
Co-authors
The 24 scholars most cited alongside Mohammad Peikari, 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 | 106 | |
| 2 | 2015 | 58 | |
| 3 | 2019 | 37 | |
| 4 | 2017 | 23 | |
| 5 | 2011 | 19 | |
| 6 | 2018 | 9 | |
| 7 | 2016 | 8 | |
| 8 | 2011 | 6 | |
| 9 | 2018 | 6 | |
| 10 | 2020 | 4 | |
| 11 | 2011 | 4 | |
| 12 | 2024 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2024 | 0 |
About Mohammad Peikari
Mohammad Peikari is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biophysics and Molecular Biology, having authored 14 papers that have together received 281 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Digital Imaging for Blood Diseases (4 papers), Cell Image Analysis Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Cardiovascular and exercise physiology (1 paper), Breast Cancer Treatment Studies (1 paper), Artificial Intelligence in Healthcare (1 paper) and Ultrasound Imaging and Elastography (1 paper). The work is most often cited by research in Biophysics (42 citations), Radiology, Nuclear Medicine and Imaging (112 citations), Artificial Intelligence (170 citations), Health Informatics (6 citations) and Computer Vision and Pattern Recognition (87 citations). Mohammad Peikari has collaborated with scholars based in Canada and United States. Frequent co-authors include Anne L. Martel, Sherine Salama, Sharon Nofech‐Mozes, Mehrdad J. Gangeh, Judit Zubovits, G. Clarke, Shazia Akbar, Gábor Fichtinger, Everette C. Burdette and András Lassó. Their work appears in journals such as Scientific Reports, Medical Physics, IEEE Transactions on Medical Imaging, PLoS ONE and European Heart Journal.
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.