Doaa Mahmoud‐Ghoneim
- Radiology, Nuclear Medicine and Imaging top 10%
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Epidemiology
- Pharmacology top 10%
- Co-authors
- Amr AminJacques D. de CertainesJean‐Marc ConstansYan ChérelLaurent LemaireMuhammed I. SyamSayel DaoudMohamed Lotfy
- Topics
- Liver Disease Diagnosis and Treatment (4 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Medical Image Segmentation Techniques (3 papers)
- Journals
- Scientific ReportsFood and Chemical ToxicologyJournal of the Science of Food and Agriculture
- Partner nations
- United Arab EmiratesFranceEgypt
In The Last Decade
Doaa Mahmoud‐Ghoneim
14 papers receiving 436 citations
Peers
Comparison fields: 5 of 105
- Radiology, Nuclear Medicine and Imaging 124
- Molecular Biology 78
- Computer Vision and Pattern Recognition 75
- Epidemiology 58
- Pharmacology 46
Countries citing papers authored by Doaa Mahmoud‐Ghoneim
This map shows the geographic impact of Doaa Mahmoud‐Ghoneim'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 Doaa Mahmoud‐Ghoneim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Doaa Mahmoud‐Ghoneim more than expected).
Fields of papers citing papers by Doaa Mahmoud‐Ghoneim
This network shows the impact of papers produced by Doaa Mahmoud‐Ghoneim. 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 Doaa Mahmoud‐Ghoneim. The network helps show where Doaa Mahmoud‐Ghoneim may publish in the future.
Co-authorship network of co-authors of Doaa Mahmoud‐Ghoneim
This figure shows the co-authorship network connecting the top 25 collaborators of Doaa Mahmoud‐Ghoneim. A scholar is included among the top collaborators of Doaa Mahmoud‐Ghoneim 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 Doaa Mahmoud‐Ghoneim. Doaa Mahmoud‐Ghoneim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 7 | |
| 3 | 36 | |
| 4 | 58 | |
| 5 | 12 | |
| 6 | 52 | |
| 7 | 49 | |
| 8 | 1 | |
| 9 | 13 | |
| 10 | 35 | |
| 11 | 48 | |
| 12 | 15 | |
| 13 | 120 | |
| 14 | 7 |
About Doaa Mahmoud‐Ghoneim
Doaa Mahmoud‐Ghoneim is a scholar working on Hepatology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 14 papers that have together received 456 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Medical Image Segmentation Techniques (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (124 citations), Pharmacology (46 citations) and Hepatology (37 citations). Doaa Mahmoud‐Ghoneim has collaborated with scholars based in United Arab Emirates, France and Egypt. Frequent co-authors include Amr Amin, Jacques D. de Certaines, Jean‐Marc Constans, Yan Chérel, Laurent Lemaire, Muhammed I. Syam, Sayel Daoud, Mohamed Lotfy, Ernest Adeghate and Peter B. Corr. Their work appears in journals such as Scientific Reports, Food and Chemical Toxicology and Journal of the Science of Food and Agriculture.
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.