George Sakellaropoulos
- Surgery top 5%
- Pulmonary and Respiratory Medicine top 5%
- Epidemiology top 10%
- Molecular Biology
- Physiology top 10%
- Co-authors
- George NikiforidisFotis KalfarentzosGeorge SkroubisNancy MeadΜαρίνα ΚαρακάντζαGeorgios NikiforidisΓεώργιος ΘεοδώρουPanagiotis Kallidonis
- Topics
- AI in cancer detection (9 papers)Urinary Bladder and Prostate Research (7 papers)Radiomics and Machine Learning in Medical Imaging (7 papers)
- Cited by
- Radiological and Ultrasound TechnologyMedical Laboratory TechnologyStatistics, Probability and Uncertainty
- Partner nations
- GreeceUnited StatesGermany
In The Last Decade
George Sakellaropoulos
91 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 160
- Surgery 758
- Pulmonary and Respiratory Medicine 498
- Epidemiology 426
- Molecular Biology 287
- Physiology 286
Countries citing papers authored by George Sakellaropoulos
This map shows the geographic impact of George Sakellaropoulos'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 George Sakellaropoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George Sakellaropoulos more than expected).
Fields of papers citing papers by George Sakellaropoulos
This network shows the impact of papers produced by George Sakellaropoulos. 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 George Sakellaropoulos. The network helps show where George Sakellaropoulos may publish in the future.
Co-authorship network of co-authors of George Sakellaropoulos
This figure shows the co-authorship network connecting the top 25 collaborators of George Sakellaropoulos. A scholar is included among the top collaborators of George Sakellaropoulos 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 George Sakellaropoulos. George Sakellaropoulos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 14 | |
| 4 | 14 | |
| 5 | 3 | |
| 6 | 40 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 20 | |
| 10 | 10 | |
| 11 | 31 | |
| 12 | 32 | |
| 13 | 35 | |
| 14 | 2 | |
| 15 | 4 | |
| 16 | 20 | |
| 17 | 9 | |
| 18 | 220 | |
| 19 | 10 | |
| 20 | 7 |
About George Sakellaropoulos
George Sakellaropoulos is a scholar working on Urology, Biophysics and Pulmonary and Respiratory Medicine, having authored 93 papers that have together received 2.5k indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Urinary Bladder and Prostate Research (7 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). The work is most often cited by research in Radiological and Ultrasound Technology (186 citations), Medical Laboratory Technology (47 citations) and Statistics, Probability and Uncertainty (145 citations). George Sakellaropoulos has collaborated with scholars based in Greece, United States and Germany. Frequent co-authors include George Nikiforidis, Fotis Kalfarentzos, George Skroubis, Nancy Mead, Μαρίνα Καρακάντζα, Georgios Nikiforidis, Γεώργιος Θεοδώρου, Panagiotis Kallidonis, Charalampos Gogos and G Theocharis. Their work appears in journals such as Journal of Biological Chemistry, Biochemistry and International Journal of Molecular Sciences.
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.