Fadila Zerka
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine
- Artificial Intelligence top 10%
- Biomedical Engineering
- Oncology
- Co-authors
- Philippe LambinRalph T. H. LeijenaarSeán WalshBenjamin MiraglioAkshayaa VaidyanathanHenry C. WoodruffWim VosSergey Primakov
- Topics
- Radiomics and Machine Learning in Medical Imaging (11 papers)Privacy-Preserving Technologies in Data (4 papers)Advanced X-ray and CT Imaging (4 papers)
- Partner nations
- NetherlandsBelgiumNorway
In The Last Decade
Fadila Zerka
14 papers receiving 639 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Radiology, Nuclear Medicine and Imaging 418
- Pulmonary and Respiratory Medicine 155
- Artificial Intelligence 151
- Biomedical Engineering 124
- Oncology 73
Countries citing papers authored by Fadila Zerka
This map shows the geographic impact of Fadila Zerka'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 Fadila Zerka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fadila Zerka more than expected).
Fields of papers citing papers by Fadila Zerka
This network shows the impact of papers produced by Fadila Zerka. 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 Fadila Zerka. The network helps show where Fadila Zerka may publish in the future.
Co-authorship network of co-authors of Fadila Zerka
This figure shows the co-authorship network connecting the top 25 collaborators of Fadila Zerka. A scholar is included among the top collaborators of Fadila Zerka 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 Fadila Zerka. Fadila Zerka 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 | 1 | |
| 3 | 1 | |
| 4 | 18 | |
| 5 | 6 | |
| 6 | 44 | |
| 7 | 15 | |
| 8 | A review in radiomics: Making personalized medicine a reality via routine imagingbreakdown → | 192 |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 80 | |
| 13 | 61 | |
| 14 | Radiomics: from qualitative to quantitative imagingbreakdown → | 224 |
About Fadila Zerka
Fadila Zerka is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 14 papers that have together received 646 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (11 papers), Privacy-Preserving Technologies in Data (4 papers) and Advanced X-ray and CT Imaging (4 papers). The work is most often cited by research in Health Informatics (70 citations), Radiology, Nuclear Medicine and Imaging (418 citations) and Otorhinolaryngology (21 citations). Fadila Zerka has collaborated with scholars based in Netherlands, Belgium and Norway. Frequent co-authors include Philippe Lambin, Ralph T. H. Leijenaar, Seán Walsh, Benjamin Miraglio, Akshayaa Vaidyanathan, Henry C. Woodruff, Wim Vos, Sergey Primakov, Abdalla Ibrahim and Turkey Refaee. Their work appears in journals such as Journal of Clinical Oncology, Scientific Reports and International Journal of Molecular Sciences.
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.