Alexandra Nikita
- Hepatology top 10%
- Hepatocellular Carcinoma Treatment and Prognosis 2
- Neurology top 10%
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- Medical Image Segmentation Techniques 5
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- Radiomics and Machine Learning in Medical Imaging 5
- MRI in cancer diagnosis 1
- Artificial Intelligence top 5%
- AI in cancer detection 8
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- Liver Disease Diagnosis and Treatment 3
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- Medical Imaging and Pathology Studies 2
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- Artificial Intelligence in Healthcare 1
- Co-authors
- Konstantina S. NikitaStavroula MougiakakouAlexis KelekisIoannis ValavanisGeorge K. MatsopoulosJohn StoitsisSpyretta GolematiGeorgia Papaioannou
In The Last Decade
Alexandra Nikita
16 papers receiving 514 citations
Peers
Comparison fields: 5 of 85
- Hepatology 82
- Neurology 81
- Computer Vision and Pattern Recognition 190
- Radiology, Nuclear Medicine and Imaging 203
- Artificial Intelligence 236
Countries citing papers authored by Alexandra Nikita
This map shows the geographic impact of Alexandra Nikita'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 Alexandra Nikita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexandra Nikita more than expected).
Fields of papers citing papers by Alexandra Nikita
This network shows the impact of papers produced by Alexandra Nikita. 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 Alexandra Nikita. The network helps show where Alexandra Nikita may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Alexandra Nikita, 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 | 2024 | 1 | |
| 2 | 2009 | 13 | |
| 3 | 2007 | 9 | |
| 4 | 2007 | 77 | |
| 5 | 2007 | 4 | |
| 6 | 2006 | 23 | |
| 7 | 2006 | 5 | |
| 8 | 2006 | 93 | |
| 9 | 2005 | 16 | |
| 10 | 2005 | 5 | |
| 11 | Cirrhosis-related intrathoracic disease. Imaging features in 1038 patients. | 2005 | 16 |
| 12 | 2005 | 3 | |
| 13 | 2004 | 39 | |
| 14 | 2003 | 179 | |
| 15 | 2002 | 15 | |
| 16 | 2002 | 66 |
About Alexandra Nikita
Alexandra Nikita is a scholar working on Hepatology, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 16 papers that have together received 564 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Image Segmentation Techniques (5 papers), Liver Disease Diagnosis and Treatment (3 papers), Hepatocellular Carcinoma Treatment and Prognosis (2 papers), Medical Imaging and Pathology Studies (2 papers), Artificial Intelligence in Healthcare (1 paper) and MRI in cancer diagnosis (1 paper). The work is most often cited by research in Hepatology (82 citations), Neurology (81 citations) and Computer Vision and Pattern Recognition (190 citations). Alexandra Nikita has collaborated with scholars based in Greece, Germany and Argentina. Frequent co-authors include Konstantina S. Nikita, Stavroula Mougiakakou, Alexis Kelekis, Ioannis Valavanis, George K. Matsopoulos, John Stoitsis, Spyretta Golemati, Georgia Papaioannou, Loukas Thanos and Katerina Malagari. Their work appears in journals such as American Journal of Roentgenology, European Radiology and IEEE Transactions on Instrumentation and Measurement.
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.