Erdi Çallı
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- Radiology practices and education
Papers in
-
- COVID-19 diagnosis using AI 8
- Radiomics and Machine Learning in Medical Imaging 4
- Radiology practices and education 2
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- Anomaly Detection Techniques and Applications 3
- Machine Learning in Healthcare 1
- Co-authors
- Bram van Ginneken (8 shared papers)Keelin Murphy (8 shared papers)Ecem Sogancioglu (5 shared papers)Kicky G. van Leeuwen (2 shared papers)Ernst T. Scholten (3 shared papers)Steven Schalekamp (3 shared papers)Matthieu Rutten (2 shared papers)Robert Herpers (1 shared paper)
- Journals
- PLoS ONE (2 papers)IEEE Transactions on Medical Imaging (1 paper)IEEE Access (1 paper)Medical Image Analysis (1 paper)European Radiology (1 paper)
- Partner nations
- Netherlands
In The Last Decade
Erdi Çallı
8 papers receiving 322 citations
Hit Papers
Peers
Comparison fields: 5 of 56
- Health Informatics 54
- Radiology, Nuclear Medicine and Imaging 270
- Artificial Intelligence 106
- Pulmonary and Respiratory Medicine 106
- Critical Care and Intensive Care Medicine 9
Countries citing papers authored by Erdi Çallı
This map shows the geographic impact of Erdi Çallı'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 Erdi Çallı with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erdi Çallı more than expected).
Fields of papers citing papers by Erdi Çallı
This network shows the impact of papers produced by Erdi Çallı. 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 Erdi Çallı. The network helps show where Erdi Çallı may publish in the future.
Co-authors
The 12 scholars most cited alongside Erdi Çallı, 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 | Deep learning for chest X-ray analysis: A survey Hit paper breakdown → | 2021 | 264 |
| 2 | 2020 | 37 | |
| 3 | 2019 | 9 | |
| 4 | 2024 | 8 | |
| 5 | 2021 | 5 | |
| 6 | 2022 | 5 | |
| 7 | 2022 | 3 | |
| 8 | FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis | 2019 | 2 |
About Erdi Çallı
Erdi Çallı is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Atomic and Molecular Physics, and Optics, having authored 8 papers that have together received 333 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (8 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Anomaly Detection Techniques and Applications (3 papers), Lung Cancer Diagnosis and Treatment (2 papers), Radiology practices and education (2 papers), Atomic and Subatomic Physics Research (1 paper), Artificial Intelligence in Healthcare and Education (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Health Informatics (54 citations), Radiology, Nuclear Medicine and Imaging (270 citations), Artificial Intelligence (106 citations), Pulmonary and Respiratory Medicine (106 citations) and Critical Care and Intensive Care Medicine (9 citations). Erdi Çallı has collaborated with scholars based in Netherlands. Frequent co-authors include Bram van Ginneken, Keelin Murphy, Ecem Sogancioglu, Kicky G. van Leeuwen, Ernst T. Scholten, Steven Schalekamp, Matthieu Rutten, Robert Herpers, Steef Kurstjens and Liesbeth Peters-Bax. Their work appears in journals such as PLoS ONE, IEEE Transactions on Medical Imaging, IEEE Access, Medical Image Analysis 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.