Hanaa Salem
- Artificial Intelligence top 5%
- Molecular Biology
- Health Information Management top 1%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Nawal El‐FishawyOmar M. ElzekiGamal AttiyaMahmoud Y. ShamsAli AlshehriIbrahim M. El‐HasnonyEmad M.S. El‐SaidA.E. Kabeel
- Topics
- Gene expression and cancer classification (7 papers)COVID-19 diagnosis using AI (4 papers)Bioinformatics and Genomic Networks (4 papers)
- Journals
- Scientific ReportsIEEE AccessSensors
- Partner nations
- EgyptSaudi ArabiaUnited States
In The Last Decade
Hanaa Salem
34 papers receiving 835 citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Artificial Intelligence 344
- Molecular Biology 184
- Health Information Management 117
- Radiology, Nuclear Medicine and Imaging 107
- Computer Vision and Pattern Recognition 95
Countries citing papers authored by Hanaa Salem
This map shows the geographic impact of Hanaa Salem'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 Hanaa Salem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hanaa Salem more than expected).
Fields of papers citing papers by Hanaa Salem
This network shows the impact of papers produced by Hanaa Salem. 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 Hanaa Salem. The network helps show where Hanaa Salem may publish in the future.
Co-authorship network of co-authors of Hanaa Salem
This figure shows the co-authorship network connecting the top 25 collaborators of Hanaa Salem. A scholar is included among the top collaborators of Hanaa Salem 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 Hanaa Salem. Hanaa Salem 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 | 6 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | An optimized capsule neural networks for tomato leaf disease classificationbreakdown → | 45 |
| 9 | 1 | |
| 10 | 13 | |
| 11 | 36 | |
| 12 | 64 | |
| 13 | 100 | |
| 14 | 43 | |
| 15 | 33 | |
| 16 | 31 | |
| 17 | 22 | |
| 18 | 21 | |
| 19 | 168 | |
| 20 | 14 |
About Hanaa Salem
Hanaa Salem is a scholar working on Issues, ethics and legal aspects, Health Information Management and Artificial Intelligence, having authored 40 papers that have together received 872 indexed citations. Recurring topics across this work include Gene expression and cancer classification (7 papers), COVID-19 diagnosis using AI (4 papers) and Bioinformatics and Genomic Networks (4 papers). The work is most often cited by research in Health Information Management (117 citations), Artificial Intelligence (344 citations) and Health Informatics (13 citations). Hanaa Salem has collaborated with scholars based in Egypt, Saudi Arabia and United States. Frequent co-authors include Nawal El‐Fishawy, Omar M. Elzeki, Gamal Attiya, Mahmoud Y. Shams, Ali Alshehri, Ibrahim M. El‐Hasnony, Emad M.S. El‐Said, A.E. Kabeel, Aboul Ella Hassanien and Mohamed Abd Elfattah. Their work appears in journals such as Scientific Reports, IEEE Access and Sensors.
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.