Peter Filev
Impact in
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- Ultrasound in Clinical Applications
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- COVID-19 diagnosis using AI
- Cardiac Imaging and Diagnostics
- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
Papers in
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- COVID-19 diagnosis using AI 5
- Advanced MRI Techniques and Applications 2
- Cardiac Imaging and Diagnostics 2
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- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis 2
- Co-authors
- Constantine A. Raptis (3 shared papers)Seth Kligerman (3 shared papers)Travis S. Henry (3 shared papers)Amar Shah (2 shared papers)Michael D. Hope (2 shared papers)Mark M. Hammer (2 shared papers)Sanjeev Bhalla (2 shared papers)Jean Jeudy (2 shared papers)
- Journals
- Medical Physics (2 papers)Radiologic Clinics of North America (1 paper)British Journal of Radiology (1 paper)Radiology Cardiothoracic Imaging (1 paper)Radiographics (1 paper)
- Partner nations
- United StatesItaly
In The Last Decade
Peter Filev
12 papers receiving 298 citations
Peers
Comparison fields: 5 of 52
- Critical Care and Intensive Care Medicine 49
- Radiology, Nuclear Medicine and Imaging 187
- Infectious Diseases 80
- Health Informatics 4
- Oncology 60
Countries citing papers authored by Peter Filev
This map shows the geographic impact of Peter Filev'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 Peter Filev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Filev more than expected).
Fields of papers citing papers by Peter Filev
This network shows the impact of papers produced by Peter Filev. 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 Peter Filev. The network helps show where Peter Filev may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Filev, 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 | 2020 | 129 | |
| 2 | 2017 | 51 | |
| 3 | 2005 | 35 | |
| 4 | 2021 | 30 | |
| 5 | 2015 | 18 | |
| 6 | 2020 | 13 | |
| 7 | 2020 | 9 | |
| 8 | 2008 | 9 | |
| 9 | 2022 | 3 | |
| 10 | 2020 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2019 | 1 | |
| 13 | 2024 | 0 | |
| 14 | 2023 | 0 |
About Peter Filev
Peter Filev is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Oncology, Artificial Intelligence and Biomedical Engineering, having authored 14 papers that have together received 301 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (5 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers), Image Retrieval and Classification Techniques (2 papers), Advanced X-ray and CT Imaging (2 papers), AI in cancer detection (2 papers), Advanced MRI Techniques and Applications (2 papers), Cardiac Imaging and Diagnostics (2 papers) and Ultrasound in Clinical Applications (2 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (49 citations), Radiology, Nuclear Medicine and Imaging (187 citations), Infectious Diseases (80 citations), Health Informatics (4 citations) and Oncology (60 citations). Peter Filev has collaborated with scholars based in United States and Italy. Frequent co-authors include Constantine A. Raptis, Seth Kligerman, Travis S. Henry, Amar Shah, Michael D. Hope, Mark M. Hammer, Sanjeev Bhalla, Jean Jeudy, Andrew J. Bierhals and Ryan G. Short. Their work appears in journals such as Medical Physics, Radiologic Clinics of North America, British Journal of Radiology, Radiology Cardiothoracic Imaging and Radiographics.
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.