Laila A. Abd-Elmegid

471 total citations
12 papers, 353 citations indexed

About

Laila A. Abd-Elmegid is a scholar working on Information Systems, Artificial Intelligence and Management Information Systems. According to data from OpenAlex, Laila A. Abd-Elmegid has authored 12 papers receiving a total of 353 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Information Systems, 4 papers in Artificial Intelligence and 3 papers in Management Information Systems. Recurrent topics in Laila A. Abd-Elmegid's work include Big Data and Business Intelligence (3 papers), Business Process Modeling and Analysis (3 papers) and Service-Oriented Architecture and Web Services (2 papers). Laila A. Abd-Elmegid is often cited by papers focused on Big Data and Business Intelligence (3 papers), Business Process Modeling and Analysis (3 papers) and Service-Oriented Architecture and Web Services (2 papers). Laila A. Abd-Elmegid collaborates with scholars based in Egypt and Malaysia. Laila A. Abd-Elmegid's co-authors include Mokhtar I. Yousef, Ahmed Sharaf Eldin, Ayman E. Khedr, Mohamed E. El-Sharkawi, Yehia Helmy, M. Thamban Nair and Amira M. Idrees and has published in prestigious journals such as SHILAP Revista de lepidopterología, Food and Chemical Toxicology and Knowledge and Information Systems.

In The Last Decade

Laila A. Abd-Elmegid

12 papers receiving 326 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Laila A. Abd-Elmegid Egypt 6 140 60 50 46 38 12 353
Yijing Lin China 9 43 0.3× 44 0.7× 10 0.2× 14 0.3× 54 1.4× 20 345
Uma Sharma India 9 44 0.3× 21 0.3× 57 1.1× 3 0.1× 78 2.1× 29 347
Shilpa Sharma India 10 24 0.2× 54 0.9× 22 0.4× 3 0.1× 67 1.8× 50 297
Shivani Kumar India 10 25 0.2× 9 0.1× 21 0.4× 12 0.3× 74 1.9× 17 403
Enrico Boldrini Italy 16 23 0.2× 27 0.5× 102 2.0× 35 0.8× 139 3.7× 59 866
Pooja Tagde Bangladesh 4 22 0.2× 55 0.9× 13 0.3× 31 0.7× 53 1.4× 4 276
Xingdong Wu China 14 55 0.4× 14 0.2× 73 1.5× 10 0.2× 182 4.8× 48 501
Ankur Rohilla India 11 115 0.8× 5 0.1× 36 0.7× 14 0.3× 83 2.2× 29 521
Jacopo Tagliabue Italy 11 51 0.4× 41 0.7× 127 2.5× 2 0.0× 102 2.7× 31 553
Qiu Gao China 9 115 0.8× 5 0.1× 68 1.4× 7 0.2× 318 8.4× 12 607

Countries citing papers authored by Laila A. Abd-Elmegid

Since Specialization
Citations

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

Fields of papers citing papers by Laila A. Abd-Elmegid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laila A. Abd-Elmegid. 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 Laila A. Abd-Elmegid. The network helps show where Laila A. Abd-Elmegid may publish in the future.

Co-authorship network of co-authors of Laila A. Abd-Elmegid

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

All Works

12 of 12 papers shown
1.
Khedr, Ayman E., et al.. (2024). A configurable mining approach for enhancing the business processes' performance. Knowledge and Information Systems. 66(4). 2537–2560. 1 indexed citations
2.
Nair, M. Thamban, et al.. (2024). Sentiment analysis model for cryptocurrency tweets using different deep learning techniques. Journal of Intelligent Systems. 33(1). 2 indexed citations
3.
Nair, M. Thamban, et al.. (2023). Prediction of Cryptocurrency Price using Time Series Data and Deep Learning Algorithms. International Journal of Advanced Computer Science and Applications. 14(8). 7 indexed citations
4.
Abd-Elmegid, Laila A., et al.. (2023). Sentiment analysis model for Airline customers’ feedback using deep learning techniques. International Journal of Engineering Business Management. 15. 7 indexed citations
5.
Eldin, Ahmed Sharaf, et al.. (2021). A Systematic Literature Review of Software Defect Prediction Using Deep Learning. Journal of Computer Science. 17(5). 490–510. 5 indexed citations
6.
Eldin, Ahmed Sharaf, et al.. (2021). Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM). PeerJ Computer Science. 7. e739–e739. 34 indexed citations
7.
Khedr, Ayman E., et al.. (2021). Adaptive model to support business process reengineering. PeerJ Computer Science. 7. e505–e505. 13 indexed citations
8.
Khedr, Ayman E., et al.. (2020). A Literature Review for Contributing Mining Approaches for Business Process Reengineering. 5(2). 60–78. 4 indexed citations
9.
Abd-Elmegid, Laila A., et al.. (2018). Stage – Specific predictive models for main prognosis measures of breast cancer. SHILAP Revista de lepidopterología. 3(2). 391–397. 3 indexed citations
10.
Abd-Elmegid, Laila A., et al.. (2018). Classification based on Clustering Model for Predicting Main Outcomes of Breast Cancer using Hyper-Parameters Optimization. International Journal of Advanced Computer Science and Applications. 9(12). 5 indexed citations
11.
12.
Abd-Elmegid, Laila A., et al.. (2010). Vertical Mining of Frequent Patterns from Uncertain Data. Computer and Information Science. 3(2). 16 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Yijing Lin Breakdown of academic impact, for papers by Uma Sharma Breakdown of academic impact, for papers by Shilpa Sharma Breakdown of academic impact, for papers by Shivani Kumar Breakdown of academic impact, for papers by Enrico Boldrini Breakdown of academic impact, for papers by Pooja Tagde Breakdown of academic impact, for papers by Xingdong Wu Breakdown of academic impact, for papers by Ankur Rohilla Breakdown of academic impact, for papers by Jacopo Tagliabue Breakdown of academic impact, for papers by Qiu Gao
Rankless by CCL
2026