Gábor Bajzik
Impact in
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- Thyroid Cancer Diagnosis and Treatment
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 12
- Advanced MRI Techniques and Applications 8
- Medical Imaging Techniques and Applications 7
- Radiation Dose and Imaging 4
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- Lung Cancer Diagnosis and Treatment 8
- Co-authors
- Imre Repa (24 shared papers)Lajos Trón (5 shared papers)Szabolcs Szakáll (5 shared papers)Olga Ésik (5 shared papers)István Sinkovics (3 shared papers)Péter Ágoston (1 shared paper)Árṕad Kov́acs (10 shared papers)Géza Sáfrány (2 shared papers)
In The Last Decade
Gábor Bajzik
48 papers receiving 376 citations
Peers
Comparison fields: 5 of 70
- Endocrinology, Diabetes and Metabolism 118
- Radiology, Nuclear Medicine and Imaging 120
- Radiation 43
- Animal Science and Zoology 39
- Otorhinolaryngology 15
Countries citing papers authored by Gábor Bajzik
This map shows the geographic impact of Gábor Bajzik'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 Gábor Bajzik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gábor Bajzik more than expected).
Fields of papers citing papers by Gábor Bajzik
This network shows the impact of papers produced by Gábor Bajzik. 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 Gábor Bajzik. The network helps show where Gábor Bajzik may publish in the future.
Co-authors
The 25 scholars most cited alongside Gábor Bajzik, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 18F-FDG PET detection of lymph node metastases in medullary thyroid carcinoma. | 2002 | 104 |
| 2 | 2004 | 35 | |
| 3 | 2001 | 21 | |
| 4 | 2016 | 19 | |
| 5 | 2003 | 15 | |
| 6 | 2015 | 14 | |
| 7 | 2015 | 13 | |
| 8 | 2004 | 11 | |
| 9 | 2011 | 11 | |
| 10 | 2003 | 11 | |
| 11 | 2004 | 10 | |
| 12 | 2010 | 9 | |
| 13 | 2020 | 9 | |
| 14 | 2018 | 9 | |
| 15 | 2008 | 7 | |
| 16 | 2008 | 7 | |
| 17 | 2017 | 7 | |
| 18 | 2001 | 7 | |
| 19 | 2018 | 6 | |
| 20 | 2022 | 4 |
About Gábor Bajzik
Gábor Bajzik is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Epidemiology, Oncology and Radiation, having authored 50 papers that have together received 386 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), Advanced MRI Techniques and Applications (8 papers), Lung Cancer Diagnosis and Treatment (8 papers), Medical Imaging Techniques and Applications (7 papers), Glioma Diagnosis and Treatment (6 papers), Advanced Radiotherapy Techniques (6 papers), Thyroid Cancer Diagnosis and Treatment (5 papers) and Radiation Dose and Imaging (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (118 citations), Radiology, Nuclear Medicine and Imaging (120 citations), Radiation (43 citations), Animal Science and Zoology (39 citations) and Otorhinolaryngology (15 citations). Gábor Bajzik has collaborated with scholars based in Hungary, Canada and Germany. Frequent co-authors include Imre Repa, Lajos Trón, Szabolcs Szakáll, Olga Ésik, István Sinkovics, Péter Ágoston, Árṕad Kov́acs, Géza Sáfrány, Janaki Hadjiev and András Szabó. Their work appears in journals such as Pathology & Oncology Research, Cancer, British Poultry Science, Clinical Neuroradiology and Strahlentherapie und Onkologie.
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.