Georgios C. Manikis
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 10%
- Ophthalmology top 5%
- Computer Vision and Pattern Recognition top 10%
- Oncology
- Co-authors
- Kostas MariasKaterina NikiforakiDimitrios I. FotiadisNikos TsiknakisEmmanouil KtistakisFábio ScarpaDimitris TheodoropoulosEleftherios Trivizakis
- Topics
- Radiomics and Machine Learning in Medical Imaging (22 papers)MRI in cancer diagnosis (21 papers)Advanced Neuroimaging Techniques and Applications (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
In The Last Decade
Georgios C. Manikis
58 papers receiving 770 citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Radiology, Nuclear Medicine and Imaging 489
- Artificial Intelligence 136
- Ophthalmology 132
- Computer Vision and Pattern Recognition 110
- Oncology 97
Countries citing papers authored by Georgios C. Manikis
This map shows the geographic impact of Georgios C. Manikis'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 Georgios C. Manikis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Georgios C. Manikis more than expected).
Fields of papers citing papers by Georgios C. Manikis
This network shows the impact of papers produced by Georgios C. Manikis. 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 Georgios C. Manikis. The network helps show where Georgios C. Manikis may publish in the future.
Co-authorship network of co-authors of Georgios C. Manikis
This figure shows the co-authorship network connecting the top 25 collaborators of Georgios C. Manikis. A scholar is included among the top collaborators of Georgios C. Manikis 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 Georgios C. Manikis. Georgios C. Manikis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 15 | |
| 8 | 14 | |
| 9 | 15 | |
| 10 | 16 | |
| 11 | 6 | |
| 12 | 28 | |
| 13 | Deep learning for diabetic retinopathy detection and classification based on fundus images: A reviewbreakdown → | 176 |
| 14 | 7 | |
| 15 | 30 | |
| 16 | 8 | |
| 17 | 11 | |
| 18 | 2 | |
| 19 | An image analysis framework for the early assessment of hypertensive retinopathy signs | 35 |
| 20 | 27 |
About Georgios C. Manikis
Georgios C. Manikis is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Oncology, having authored 65 papers that have together received 795 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (22 papers), MRI in cancer diagnosis (21 papers) and Advanced Neuroimaging Techniques and Applications (10 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (489 citations), Health Information Management (85 citations) and Health Informatics (23 citations). Georgios C. Manikis has collaborated with scholars based in Greece, Portugal and Italy. Frequent co-authors include Kostas Marias, Katerina Nikiforaki, Dimitrios I. Fotiadis, Nikos Tsiknakis, Emmanouil Ktistakis, Fábio Scarpa, Dimitris Theodoropoulos, Eleftherios Trivizakis, Antonios Drevelegas and Vangelis Sakkalis. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.