Dariush Askari
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
- Radiation Dose and Imaging
Papers in
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- Radiomics and Machine Learning in Medical Imaging 4
- COVID-19 diagnosis using AI 3
- Medical Imaging Techniques and Applications 3
- Radiation Dose and Imaging 2
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- Advanced X-ray and CT Imaging 5
- Co-authors
- Habib Zaidi (5 shared papers)Hossein Arabi (5 shared papers)Yazdan Salimi (5 shared papers)Isaac Shiri (5 shared papers)Hamid Abdollahi (4 shared papers)Amirhossein Sanaat (4 shared papers)Azadeh Akhavanallaf (4 shared papers)Saleh Sandoughdaran (4 shared papers)
- Journals
- International Journal of Imaging Systems and Technology (1 paper)Computers in Biology and Medicine (1 paper)Insights into Imaging (1 paper)European Radiology (1 paper)
- Partner nations
- IranSwitzerlandNetherlands
In The Last Decade
Dariush Askari
7 papers receiving 227 citations
Peers
Comparison fields: 5 of 52
- Health Informatics 31
- Radiology, Nuclear Medicine and Imaging 197
- Critical Care and Intensive Care Medicine 11
- Biomedical Engineering 88
- Artificial Intelligence 40
Countries citing papers authored by Dariush Askari
This map shows the geographic impact of Dariush Askari'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 Dariush Askari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dariush Askari more than expected).
Fields of papers citing papers by Dariush Askari
This network shows the impact of papers produced by Dariush Askari. 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 Dariush Askari. The network helps show where Dariush Askari may publish in the future.
Co-authors
The 25 scholars most cited alongside Dariush Askari, 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 | 2021 | 72 | |
| 2 | 2020 | 70 | |
| 3 | 2021 | 37 | |
| 4 | 2021 | 27 | |
| 5 | 2022 | 19 | |
| 6 | 2022 | 3 | |
| 7 | 2020 | 1 |
About Dariush Askari
Dariush Askari is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Pulmonary and Respiratory Medicine, Otorhinolaryngology and Artificial Intelligence, having authored 7 papers that have together received 229 indexed citations. Recurring topics across this work include Advanced X-ray and CT Imaging (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), COVID-19 diagnosis using AI (3 papers), Medical Imaging Techniques and Applications (3 papers), Lung Cancer Diagnosis and Treatment (2 papers), Radiation Dose and Imaging (2 papers), AI in cancer detection (1 paper) and Head and Neck Cancer Studies (1 paper). The work is most often cited by research in Health Informatics (31 citations), Radiology, Nuclear Medicine and Imaging (197 citations), Critical Care and Intensive Care Medicine (11 citations), Biomedical Engineering (88 citations) and Artificial Intelligence (40 citations). Dariush Askari has collaborated with scholars based in Iran, Switzerland and Netherlands. Frequent co-authors include Habib Zaidi, Hossein Arabi, Yazdan Salimi, Isaac Shiri, Hamid Abdollahi, Amirhossein Sanaat, Azadeh Akhavanallaf, Saleh Sandoughdaran, Ghasem Hajianfar and Kiara Rezaei‐Kalantari. Their work appears in journals such as International Journal of Imaging Systems and Technology, Computers in Biology and Medicine, Insights into Imaging and European Radiology.
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.