Reut Anconina
- Pulmonary and Respiratory Medicine
- Radiology, Nuclear Medicine and Imaging
- Oncology
- Neurology
- Epidemiology
- Co-authors
- Ur MetserPatrick Veit‐HaibachClaudia OrtegaNir HodRebecca WongAmy LiuRosalyn A. JuergensDavid Laidley
- Topics
- Radiomics and Machine Learning in Medical Imaging (8 papers)Prostate Cancer Treatment and Research (7 papers)Radiopharmaceutical Chemistry and Applications (6 papers)
- Partner nations
- CanadaUnited StatesIsrael
In The Last Decade
Reut Anconina
32 papers receiving 304 citations
Peers
Comparison fields: 5 of 53
- Pulmonary and Respiratory Medicine 120
- Radiology, Nuclear Medicine and Imaging 108
- Oncology 90
- Neurology 72
- Epidemiology 56
Countries citing papers authored by Reut Anconina
This map shows the geographic impact of Reut Anconina'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 Reut Anconina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reut Anconina more than expected).
Fields of papers citing papers by Reut Anconina
This network shows the impact of papers produced by Reut Anconina. 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 Reut Anconina. The network helps show where Reut Anconina may publish in the future.
Co-authorship network of co-authors of Reut Anconina
This figure shows the co-authorship network connecting the top 25 collaborators of Reut Anconina. A scholar is included among the top collaborators of Reut Anconina 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 Reut Anconina. Reut Anconina is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 14 | |
| 3 | 13 | |
| 4 | 5 | |
| 5 | 11 | |
| 6 | 12 | |
| 7 | 55 | |
| 8 | 20 | |
| 9 | 3 | |
| 10 | 11 | |
| 11 | 22 | |
| 12 | The contribution of multiparametric pelvic and whole body MR to the interpretation of 18F-fluoromethylcholine (FCH) or 68Ga-HBED-CC PSMA-11 (PSMA) PET/CT in the detection of pelvic recurrence or distant metastases in patients with biochemical failure following radical prostatectomy. | 2 |
| 13 | 4 | |
| 14 | 3 | |
| 15 | 3 | |
| 16 | 2 | |
| 17 | 8 | |
| 18 | 13 | |
| 19 | 2 | |
| 20 | 14 |
About Reut Anconina
Reut Anconina is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Pulmonary and Respiratory Medicine, having authored 32 papers that have together received 305 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), Prostate Cancer Treatment and Research (7 papers) and Radiopharmaceutical Chemistry and Applications (6 papers). The work is most often cited by research in Neurology (72 citations), Radiology, Nuclear Medicine and Imaging (108 citations) and Pulmonary and Respiratory Medicine (120 citations). Reut Anconina has collaborated with scholars based in Canada, United States and Israel. Frequent co-authors include Ur Metser, Patrick Veit‐Haibach, Claudia Ortega, Nir Hod, Rebecca Wong, Amy Liu, Rosalyn A. Juergens, David Laidley, Ilan Shelef and Sten Myrehaug. Their work appears in journals such as Journal of Clinical Oncology, 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.