Arabi Keshk

1.2k total citations · 1 hit paper
67 papers, 743 citations indexed

About

Arabi Keshk is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Arabi Keshk has authored 67 papers receiving a total of 743 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 22 papers in Information Systems and 16 papers in Computer Networks and Communications. Recurrent topics in Arabi Keshk's work include Cloud Computing and Resource Management (8 papers), AI in cancer detection (7 papers) and IoT and Edge/Fog Computing (6 papers). Arabi Keshk is often cited by papers focused on Cloud Computing and Resource Management (8 papers), AI in cancer detection (7 papers) and IoT and Edge/Fog Computing (6 papers). Arabi Keshk collaborates with scholars based in Egypt, France and China. Arabi Keshk's co-authors include Medhat A. Tawfeek, Ashraf B. El-Sisi, Fawzy A. Torkey, Mohamed Sakr, Abeer Saber, Osama M. Abo-Seida, Huiling Chen, Mahmoud Hussein, Shaimaa Mahmoud and Nabil A. Ismail and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Arabi Keshk

59 papers receiving 683 citations

Hit Papers

A Novel Deep-Learning Model for Automatic Detection and C... 2021 2026 2022 2024 2021 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique
    2021 266 citations Mohamed Sakr, Arabi Keshk et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Arabi Keshk Egypt 8 347 316 298 174 99 67 743
Diyar Qader Zeebaree Iraq 14 224 0.6× 122 0.4× 108 0.4× 108 0.6× 89 0.9× 23 508
B. Surendiran India 13 307 0.9× 147 0.5× 114 0.4× 71 0.4× 117 1.2× 54 540
A. Kumaravel India 11 245 0.7× 300 0.9× 176 0.6× 50 0.3× 93 0.9× 51 824
Muhammad Sardaraz Pakistan 13 277 0.8× 370 1.2× 315 1.1× 37 0.2× 115 1.2× 35 699
Mohammad Abrar Pakistan 15 216 0.6× 81 0.3× 100 0.3× 131 0.8× 163 1.6× 41 546
K. Lakshmanan India 13 282 0.8× 118 0.4× 82 0.3× 119 0.7× 114 1.2× 38 555
Sahalu B. Junaidu Nigeria 11 187 0.5× 104 0.3× 87 0.3× 59 0.3× 47 0.5× 39 380
Tolga Ensarı Türkiye 11 497 1.4× 222 0.7× 58 0.2× 109 0.6× 80 0.8× 44 763
Mohd Arfian Ismail Malaysia 13 239 0.7× 122 0.4× 127 0.4× 32 0.2× 47 0.5× 66 510
Vani Rajasekar India 13 134 0.4× 112 0.4× 129 0.4× 70 0.4× 156 1.6× 47 508

Countries citing papers authored by Arabi Keshk

Since Specialization
Citations

This map shows the geographic impact of Arabi Keshk'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 Arabi Keshk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arabi Keshk more than expected).

Fields of papers citing papers by Arabi Keshk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arabi Keshk. 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 Arabi Keshk. The network helps show where Arabi Keshk may publish in the future.

Co-authorship network of co-authors of Arabi Keshk

This figure shows the co-authorship network connecting the top 25 collaborators of Arabi Keshk. A scholar is included among the top collaborators of Arabi Keshk 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 Arabi Keshk. Arabi Keshk is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Keshk, Arabi, et al.. (2025). Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization. Applied Sciences. 15(2). 489–489. 3 indexed citations
2.
3.
Hussein, Mahmoud, et al.. (2023). A framework for predicting breast cancer recurrence. Expert Systems with Applications. 240. 122641–122641. 6 indexed citations
4.
5.
Keshk, Arabi, et al.. (2023). A Comparative Study for Different Resampling Techniques for Imbalanced datasets. 10(3). 147–156. 4 indexed citations
6.
Mohamed, Eman, et al.. (2023). Context-aware recommender system for multi-user smart home. International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering. 13(3). 3192–3192. 3 indexed citations
7.
8.
Saad, Omar M., et al.. (2023). Prediction Model for Peak Ground Acceleration Using Deep Learning. 10(3). 175–183. 1 indexed citations
9.
Mohammed, Ammar, et al.. (2022). A Fuzzy-Crisp Frequent Concept Lattice Generation Algorithm. 75–80. 1 indexed citations
10.
Keshk, Arabi, et al.. (2022). A hybrid swarm intelligence feature selection approach based on time-varying transition parameter. International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering. 13(1). 781–781. 2 indexed citations
11.
Mahmoud, Shaimaa, et al.. (2022). Cardiovascular Disease Prediction Using Modified Version of ResNet-50 Model. 7. 18–24. 2 indexed citations
12.
Mahmoud, Shaimaa, et al.. (2022). Heart Disease Prediction Using Modified Version of LeNet-5 Model. International Journal of Intelligent Systems and Applications. 14(6). 1–12. 8 indexed citations
13.
Mahmoud, Shaimaa, Mahmoud Hussein, & Arabi Keshk. (2020). Predicting Future Products Rate using Machine Learning Algorithms. International Journal of Intelligent Systems and Applications. 12(5). 41–51. 4 indexed citations
14.
Mohamed, Eman, et al.. (2019). Enhanced PROBCONS for Multiple Sequence Alignment in Cloud Computing. International Journal of Information Technology and Computer Science. 11(9). 38–47. 2 indexed citations
15.
Mohamed, Eman, et al.. (2018). Comparative Analysis of Multiple Sequence Alignment Tools. International Journal of Information Technology and Computer Science. 10(8). 24–30. 5 indexed citations
16.
El-Sisi, Ashraf B., et al.. (2017). Extend Web Service Security Negotiation Framework in Privacy. International Journal of Information Technology and Computer Science. 9(8). 30–39. 1 indexed citations
17.
El-Sisi, Ashraf B., et al.. (2016). Improving Matching Web Service Security Policy Based on Semantics. International Journal of Information Technology and Computer Science. 8(12). 62–74. 2 indexed citations
18.
Tawfeek, Medhat A., Ashraf B. El-Sisi, Arabi Keshk, & Fawzy A. Torkey. (2015). Cloud task scheduling based on ant colony optimization.. The International Arab Journal of Information Technology. 12. 129–137. 49 indexed citations
19.
Keshk, Arabi, et al.. (2015). Memetic Algorithm For Solving University Course Timetabling Problem. 2 indexed citations
20.
Keshk, Arabi, et al.. (2012). Improve performance of enterprises information portal using RFC and IDOC technique. 1 indexed citations

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.

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