Heba Abdel-Nabi
- Information Systems top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Management Information Systems
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Samar Al-SaqqaArafat AwajanMostafa Z. AliAli Al‐HajPonnuthurai Nagaratnam SuganthanRami AlazraiMohammad I. DaoudGhazi Al‐Naymat
- Topics
- AI in cancer detection (4 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Advanced Multi-Objective Optimization Algorithms (3 papers)
In The Last Decade
Heba Abdel-Nabi
15 papers receiving 297 citations
Hit Papers
Peers
Comparison fields: 5 of 78
- Information Systems 116
- Artificial Intelligence 116
- Computer Vision and Pattern Recognition 52
- Management Information Systems 28
- Radiology, Nuclear Medicine and Imaging 24
Countries citing papers authored by Heba Abdel-Nabi
This map shows the geographic impact of Heba Abdel-Nabi'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 Heba Abdel-Nabi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heba Abdel-Nabi more than expected).
Fields of papers citing papers by Heba Abdel-Nabi
This network shows the impact of papers produced by Heba Abdel-Nabi. 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 Heba Abdel-Nabi. The network helps show where Heba Abdel-Nabi may publish in the future.
Co-authorship network of co-authors of Heba Abdel-Nabi
This figure shows the co-authorship network connecting the top 25 collaborators of Heba Abdel-Nabi. A scholar is included among the top collaborators of Heba Abdel-Nabi 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 Heba Abdel-Nabi. Heba Abdel-Nabi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 12 | |
| 5 | 8 | |
| 6 | 22 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 10 | |
| 11 | 14 | |
| 12 | 4 | |
| 13 | 12 | |
| 14 | Agile Software Development: Methodologies and Trendsbreakdown → | 175 |
| 15 | 6 | |
| 16 | 36 | |
| 17 | 1 |
About Heba Abdel-Nabi
Heba Abdel-Nabi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 17 papers that have together received 312 indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). The work is most often cited by research in Information Systems (116 citations), Computer Science Applications (21 citations) and Software (14 citations). Heba Abdel-Nabi has collaborated with scholars based in Jordan, Singapore and Qatar. Frequent co-authors include Samar Al-Saqqa, Arafat Awajan, Mostafa Z. Ali, Ali Al‐Haj, Ponnuthurai Nagaratnam Suganthan, Rami Alazrai, Mohammad I. Daoud, Ghazi Al‐Naymat, Nadim Obeid and Robert G. Reynolds. Their work appears in journals such as IEEE Access, Information Sciences and Biomedical Signal Processing and Control.
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.