Gitit Lavy-Shahaf
Impact in
- Genetics top 10%
- Glioma Diagnosis and Treatment
Papers in
- Genetics 12
- Glioma Diagnosis and Treatment 12
-
- Radiomics and Machine Learning in Medical Imaging 4
- Radiopharmaceutical Chemistry and Applications 3
- Medical Imaging Techniques and Applications 2
- Co-authors
- Matthew T. Ballo (9 shared papers)Zéev Bomzon (7 shared papers)Noa Urman (10 shared papers)Steven A. Toms (4 shared papers)Jai Grewal (1 shared paper)Aaron Rulseh (4 shared papers)Patrick R. Conlon (4 shared papers)Adrian Kinzel (6 shared papers)
- Journals
- International Journal of Radiation Oncology*Biology*Physics (6 papers)Neuro-Oncology (5 papers)Retrovirology (1 paper)Journal of Clinical Pathology (1 paper)Clinical Trials (1 paper)
- Partner nations
- United StatesSwitzerlandCzechia
In The Last Decade
Gitit Lavy-Shahaf
18 papers receiving 250 citations
Peers
Comparison fields: 5 of 53
- Genetics 125
- Structural Biology 6
- Virology 13
- Cancer Research 26
- Modeling and Simulation 7
Countries citing papers authored by Gitit Lavy-Shahaf
This map shows the geographic impact of Gitit Lavy-Shahaf'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 Gitit Lavy-Shahaf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gitit Lavy-Shahaf more than expected).
Fields of papers citing papers by Gitit Lavy-Shahaf
This network shows the impact of papers produced by Gitit Lavy-Shahaf. 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 Gitit Lavy-Shahaf. The network helps show where Gitit Lavy-Shahaf may publish in the future.
Co-authors
The 25 scholars most cited alongside Gitit Lavy-Shahaf, 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 | 2019 | 103 | |
| 2 | 2023 | 46 | |
| 3 | 2021 | 32 | |
| 4 | 2014 | 27 | |
| 5 | 2020 | 16 | |
| 6 | 2017 | 9 | |
| 7 | 2019 | 7 | |
| 8 | 2023 | 4 | |
| 9 | 2017 | 4 | |
| 10 | 2018 | 2 | |
| 11 | 2025 | 1 | |
| 12 | 2023 | 1 | |
| 13 | 2017 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2018 | 1 | |
| 16 | 2019 | 1 | |
| 17 | 2018 | 1 | |
| 18 | 2020 | 1 | |
| 19 | 2018 | 0 |
About Gitit Lavy-Shahaf
Gitit Lavy-Shahaf is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging, Cancer Research, Modeling and Simulation and Molecular Biology, having authored 19 papers that have together received 258 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (12 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Radiopharmaceutical Chemistry and Applications (3 papers), Cancer Genomics and Diagnostics (2 papers), Mathematical Biology Tumor Growth (2 papers), Medical Imaging Techniques and Applications (2 papers), Neuroscience and Neural Engineering (1 paper) and Advanced Radiotherapy Techniques (1 paper). The work is most often cited by research in Genetics (125 citations), Structural Biology (6 citations), Virology (13 citations), Cancer Research (26 citations) and Modeling and Simulation (7 citations). Gitit Lavy-Shahaf has collaborated with scholars based in United States, Switzerland and Czechia. Frequent co-authors include Matthew T. Ballo, Zéev Bomzon, Noa Urman, Steven A. Toms, Jai Grewal, Aaron Rulseh, Patrick R. Conlon, Adrian Kinzel, Josef Vymazal and Sylvie Amu. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Neuro-Oncology, Retrovirology, Journal of Clinical Pathology and Clinical Trials.
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.