Sharbell Hashoul
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Pulmonary and Respiratory Medicine
- Neurology
- Co-authors
- Rami Ben‐AriPavel KisilevBoris GinsburgRon KimmelSharon AlpertLeonid KarlinskyElla BarkanAyelet Akselrod-Ballin
- Topics
- AI in cancer detection (8 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Digital Radiography and Breast Imaging (3 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- The American Journal of CardiologyIBM Journal of Research and DevelopmentJournal of Medical Imaging and Radiation Oncology
- Partner nations
- IsraelAustraliaUnited States
In The Last Decade
Sharbell Hashoul
10 papers receiving 245 citations
Peers
Comparison fields: 5 of 37
- Artificial Intelligence 204
- Radiology, Nuclear Medicine and Imaging 175
- Computer Vision and Pattern Recognition 81
- Pulmonary and Respiratory Medicine 40
- Neurology 24
Countries citing papers authored by Sharbell Hashoul
This map shows the geographic impact of Sharbell Hashoul'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 Sharbell Hashoul with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sharbell Hashoul more than expected).
Fields of papers citing papers by Sharbell Hashoul
This network shows the impact of papers produced by Sharbell Hashoul. 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 Sharbell Hashoul. The network helps show where Sharbell Hashoul may publish in the future.
Co-authorship network of co-authors of Sharbell Hashoul
This figure shows the co-authorship network connecting the top 25 collaborators of Sharbell Hashoul. A scholar is included among the top collaborators of Sharbell Hashoul 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 Sharbell Hashoul. Sharbell Hashoul is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 37 | |
| 3 | 28 | |
| 4 | 52 | |
| 5 | 24 | |
| 6 | 63 | |
| 7 | 6 | |
| 8 | 31 | |
| 9 | 2 | |
| 10 | 8 |
About Sharbell Hashoul
Sharbell Hashoul is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Critical Care and Intensive Care Medicine, having authored 10 papers that have together received 256 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Digital Radiography and Breast Imaging (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (175 citations), Artificial Intelligence (204 citations) and Computer Vision and Pattern Recognition (81 citations). Sharbell Hashoul has collaborated with scholars based in Israel, Australia and United States. Frequent co-authors include Rami Ben‐Ari, Pavel Kisilev, Boris Ginsburg, Ron Kimmel, Sharon Alpert, Leonid Karlinsky, Ella Barkan, Ayelet Akselrod-Ballin, Boaz Ophir and Eugene Walach. Their work appears in journals such as The American Journal of Cardiology, IBM Journal of Research and Development and Journal of Medical Imaging and Radiation Oncology.
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.