Aydın Demircioğlu
- Radiology, Nuclear Medicine and Imaging top 2%
- Pulmonary and Respiratory Medicine
- Biomedical Engineering
- Artificial Intelligence top 10%
- Surgery
- Co-authors
- Felix NensaChristoph RischplerLale UmutluMichael ForstingKen HerrmannBenedikt M. SchaarschmidtJohannes GrueneisenGerald Antoch
- Topics
- Radiomics and Machine Learning in Medical Imaging (25 papers)Advanced X-ray and CT Imaging (15 papers)AI in cancer detection (10 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingPulmonary and Respiratory Medicine
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Aydın Demircioğlu
51 papers receiving 851 citations
Peers
Comparison fields: 5 of 120
- Radiology, Nuclear Medicine and Imaging 545
- Pulmonary and Respiratory Medicine 186
- Biomedical Engineering 168
- Artificial Intelligence 132
- Surgery 113
Countries citing papers authored by Aydın Demircioğlu
This map shows the geographic impact of Aydın Demircioğlu'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 Aydın Demircioğlu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aydın Demircioğlu more than expected).
Fields of papers citing papers by Aydın Demircioğlu
This network shows the impact of papers produced by Aydın Demircioğlu. 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 Aydın Demircioğlu. The network helps show where Aydın Demircioğlu may publish in the future.
Co-authorship network of co-authors of Aydın Demircioğlu
This figure shows the co-authorship network connecting the top 25 collaborators of Aydın Demircioğlu. A scholar is included among the top collaborators of Aydın Demircioğlu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aydın Demircioğlu. Aydın Demircioğlu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 1 | |
| 3 | 32 | |
| 4 | 2 | |
| 5 | 7 | |
| 6 | 32 | |
| 7 | 6 | |
| 8 | 2 | |
| 9 | 21 | |
| 10 | 6 | |
| 11 | 10 | |
| 12 | 58 | |
| 13 | 12 | |
| 14 | 37 | |
| 15 | 68 | |
| 16 | 7 | |
| 17 | 4 | |
| 18 | 15 | |
| 19 | 18 | |
| 20 | 3 |
About Aydın Demircioğlu
Aydın Demircioğlu is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Internal Medicine, having authored 53 papers that have together received 861 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (25 papers), Advanced X-ray and CT Imaging (15 papers) and AI in cancer detection (10 papers). The work is most often cited by research in Health Informatics (64 citations), Radiology, Nuclear Medicine and Imaging (545 citations) and Pulmonary and Respiratory Medicine (186 citations). Aydın Demircioğlu has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Felix Nensa, Christoph Rischpler, Lale Umutlu, Michael Forsting, Ken Herrmann, Benedikt M. Schaarschmidt, Johannes Grueneisen, Gerald Antoch, Johannes Haubold and Kai Naßenstein. Their work appears in journals such as PLoS ONE, Scientific Reports and BioMed Research International.
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.