Fatima Dakalbab
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Signal Processing top 10%
- Information Systems top 10%
- Control and Systems Engineering top 10%
- Co-authors
- Manar Abu TalibQassim NasirAli Bou NassifAnissa M. BettayebSohail AbbasMaâmar BettayebChaouki GhenaïNoura Metawa
- Topics
- Crime Patterns and Interventions (2 papers)Artificial Intelligence in Healthcare and Education (2 papers)Topic Modeling (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessJournal of King Saud University - Computer and Information Sciences
- Partner nations
- United Arab EmiratesLatvia
In The Last Decade
Fatima Dakalbab
10 papers receiving 481 citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 291
- Computer Networks and Communications 213
- Signal Processing 92
- Information Systems 82
- Control and Systems Engineering 79
Countries citing papers authored by Fatima Dakalbab
This map shows the geographic impact of Fatima Dakalbab'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 Fatima Dakalbab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fatima Dakalbab more than expected).
Fields of papers citing papers by Fatima Dakalbab
This network shows the impact of papers produced by Fatima Dakalbab. 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 Fatima Dakalbab. The network helps show where Fatima Dakalbab may publish in the future.
Co-authorship network of co-authors of Fatima Dakalbab
This figure shows the co-authorship network connecting the top 25 collaborators of Fatima Dakalbab. A scholar is included among the top collaborators of Fatima Dakalbab 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 Fatima Dakalbab. Fatima Dakalbab 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 | 3 | |
| 3 | 1 | |
| 4 | 34 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 19 | |
| 8 | 35 | |
| 9 | 0 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 82 | |
| 13 | Machine Learning for Anomaly Detection: A Systematic Reviewbreakdown → | 342 |
About Fatima Dakalbab
Fatima Dakalbab is a scholar working on Health Informatics, Artificial Intelligence and Computer Networks and Communications, having authored 13 papers that have together received 523 indexed citations. Recurring topics across this work include Crime Patterns and Interventions (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Health Informatics (19 citations), Computer Networks and Communications (213 citations) and Artificial Intelligence (291 citations). Fatima Dakalbab has collaborated with scholars based in United Arab Emirates and Latvia. Frequent co-authors include Manar Abu Talib, Qassim Nasir, Ali Bou Nassif, Anissa M. Bettayeb, Sohail Abbas, Maâmar Bettayeb, Chaouki Ghenaï and Noura Metawa. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Journal of King Saud University - Computer and Information 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.