Ecem Sogancioglu
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
-
- 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 5
-
- Lung Cancer Diagnosis and Treatment 3
- Co-authors
- Bram van Ginneken (8 shared papers)Keelin Murphy (7 shared papers)Erdi Çallı (5 shared papers)Kicky G. van Leeuwen (1 shared paper)Ernst T. Scholten (4 shared papers)Steven Schalekamp (2 shared papers)Jesus Lago (2 shared papers)Bart De Schutter (2 shared papers)
- Journals
- IEEE Transactions on Medical Imaging (2 papers)Medical Physics (1 paper)IEEE Transactions on Control Systems Technology (1 paper)IEEE Access (1 paper)Medical Image Analysis (1 paper)
- Partner nations
- NetherlandsUnited StatesGermany
In The Last Decade
Ecem Sogancioglu
10 papers receiving 368 citations
Hit Papers
Peers
Comparison fields: 5 of 68
- Health Informatics 48
- Radiology, Nuclear Medicine and Imaging 283
- Pulmonary and Respiratory Medicine 122
- Artificial Intelligence 112
- Computer Vision and Pattern Recognition 44
Countries citing papers authored by Ecem Sogancioglu
This map shows the geographic impact of Ecem Sogancioglu'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 Ecem Sogancioglu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ecem Sogancioglu more than expected).
Fields of papers citing papers by Ecem Sogancioglu
This network shows the impact of papers produced by Ecem Sogancioglu. 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 Ecem Sogancioglu. The network helps show where Ecem Sogancioglu may publish in the future.
Co-authors
The 21 scholars most cited alongside Ecem Sogancioglu, 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 | 2022 | 21 | |
| 4 | 2020 | 16 | |
| 5 | 2022 | 11 | |
| 6 | 2019 | 9 | |
| 7 | 2024 | 8 | |
| 8 | 2019 | 6 | |
| 9 | 2022 | 5 | |
| 10 | FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis | 2019 | 2 |
About Ecem Sogancioglu
Ecem Sogancioglu is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Control and Systems Engineering, Computer Vision and Pattern Recognition and Atomic and Molecular Physics, and Optics, having authored 10 papers that have together received 379 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (8 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Lung Cancer Diagnosis and Treatment (3 papers), Microgrid Control and Optimization (2 papers), Atomic and Subatomic Physics Research (2 papers), Anomaly Detection Techniques and Applications (2 papers), Smart Grid Energy Management (2 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Health Informatics (48 citations), Radiology, Nuclear Medicine and Imaging (283 citations), Pulmonary and Respiratory Medicine (122 citations), Artificial Intelligence (112 citations) and Computer Vision and Pattern Recognition (44 citations). Ecem Sogancioglu has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include Bram van Ginneken, Keelin Murphy, Erdi Çallı, Kicky G. van Leeuwen, Ernst T. Scholten, Steven Schalekamp, Jesus Lago, Bart De Schutter, Friso G. Heslinga and Mitko Veta. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Physics, IEEE Transactions on Control Systems Technology, IEEE Access and Medical Image Analysis.
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.