Radwa Elshawi

1.3k total citations
26 papers, 765 citations indexed

About

Radwa Elshawi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Radwa Elshawi has authored 26 papers receiving a total of 765 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 6 papers in Information Systems. Recurrent topics in Radwa Elshawi's work include Machine Learning and Data Classification (6 papers), Machine Learning in Healthcare (4 papers) and Graph Theory and Algorithms (4 papers). Radwa Elshawi is often cited by papers focused on Machine Learning and Data Classification (6 papers), Machine Learning in Healthcare (4 papers) and Graph Theory and Algorithms (4 papers). Radwa Elshawi collaborates with scholars based in Saudi Arabia, Estonia and United States. Radwa Elshawi's co-authors include Sherif Sakr, Mouaz H. Al‐Mallah, Amjad Ahmed, Waqas Qureshi, Ahmed Barnawi, Steven J. Keteyian, Clinton A. Brawner, Michael J. Blaha, Abdul Wahab and Omar Batarfi and has published in prestigious journals such as Journal of the American College of Cardiology, PLoS ONE and Scientific Reports.

In The Last Decade

Radwa Elshawi

26 papers receiving 740 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Radwa Elshawi Saudi Arabia 12 326 137 126 81 66 26 765
Ernesto Iadanza Italy 17 133 0.4× 149 1.1× 163 1.3× 53 0.7× 44 0.7× 77 878
Cristina Soguero-Ruíz Spain 18 416 1.3× 76 0.6× 133 1.1× 47 0.6× 104 1.6× 81 1.1k
Guilan Kong China 20 360 1.1× 80 0.6× 159 1.3× 53 0.7× 183 2.8× 57 1.1k
Bo Jin China 18 335 1.0× 116 0.8× 125 1.0× 66 0.8× 159 2.4× 52 1.0k
Haohui Lu Australia 12 272 0.8× 28 0.2× 195 1.5× 55 0.7× 82 1.2× 27 836
Jinwook Choi South Korea 17 272 0.8× 64 0.5× 103 0.8× 65 0.8× 49 0.7× 93 1.0k
William Marsh United Kingdom 20 279 0.9× 48 0.4× 71 0.6× 305 3.8× 61 0.9× 71 1.2k
Honghan Wu United Kingdom 18 528 1.6× 35 0.3× 159 1.3× 76 0.9× 125 1.9× 77 1.1k
António Abelha Portugal 14 257 0.8× 38 0.3× 307 2.4× 151 1.9× 43 0.7× 154 921
Rod Hose United Kingdom 12 78 0.2× 193 1.4× 95 0.8× 37 0.5× 41 0.6× 24 599

Countries citing papers authored by Radwa Elshawi

Since Specialization
Citations

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

Fields of papers citing papers by Radwa Elshawi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Radwa Elshawi

This figure shows the co-authorship network connecting the top 25 collaborators of Radwa Elshawi. A scholar is included among the top collaborators of Radwa Elshawi 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 Radwa Elshawi. Radwa Elshawi 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.
Elshawi, Radwa, Sherif Sakr, Mouaz H. Al‐Mallah, et al.. (2024). FIT calculator: a multi-risk prediction framework for medical outcomes using cardiorespiratory fitness data. Scientific Reports. 14(1). 8745–8745. 3 indexed citations
2.
Voormansik, Kaupo, et al.. (2022). Exploiting time series of Sentinel-1 and Sentinel-2 to detect grassland mowing events using deep learning with reject region. Scientific Reports. 12(1). 983–983. 24 indexed citations
3.
Elshawi, Radwa & Sherif Sakr. (2022). TPE-AutoClust: A Tree-based Pipline Ensemble Framework for Automated Clustering. 1144–1153. 5 indexed citations
4.
Elshawi, Radwa & Sherif Sakr. (2022). cSmartML-Glassbox: Increasing Transparency and Controllability in Automated Clustering. 47–54. 2 indexed citations
5.
Elshawi, Radwa, Abdul Wahab, Ahmed Barnawi, & Sherif Sakr. (2021). DLBench: a comprehensive experimental evaluation of deep learning frameworks. Cluster Computing. 24(3). 2017–2038. 40 indexed citations
6.
Elshawi, Radwa, et al.. (2020). Interpretability in healthcare: A comparative study of local machine learning interpretability techniques. Computational Intelligence. 37(4). 1633–1650. 96 indexed citations
7.
Elshawi, Radwa, Mouaz H. Al‐Mallah, & Sherif Sakr. (2019). On the interpretability of machine learning-based model for predicting hypertension. BMC Medical Informatics and Decision Making. 19(1). 146–146. 175 indexed citations
8.
Elshawi, Radwa, et al.. (2019). Predictors of in-hospital length of stay among cardiac patients: A machine learning approach. International Journal of Cardiology. 288. 140–147. 112 indexed citations
9.
Elshawi, Radwa, et al.. (2019). A Decision Support Framework for AutoML Systems: A Meta-Learning Approach. 97–106. 17 indexed citations
10.
Sakr, Sherif, Radwa Elshawi, Amjad Ahmed, et al.. (2018). Using machine learning on cardiorespiratory fitness data for predicting hypertension: The Henry Ford ExercIse Testing (FIT) Project. PLoS ONE. 13(4). e0195344–e0195344. 86 indexed citations
11.
Sakr, Sherif, Radwa Elshawi, Amjad Ahmed, et al.. (2017). Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project. BMC Medical Informatics and Decision Making. 17(1). 174–174. 69 indexed citations
12.
Al‐Mallah, Mouaz H., Radwa Elshawi, Amjad Ahmed, et al.. (2017). Using Machine Learning to Define the Association between Cardiorespiratory Fitness and All-Cause Mortality (from the Henry Ford Exercise Testing Project). The American Journal of Cardiology. 120(11). 2078–2084. 19 indexed citations
13.
Al‐Mallah, Mouaz H., Amjad Ahmed, Waqas Qureshi, et al.. (2017). USING MACHINE LEARNING TO DEFINE THE ASSOCIATION BETWEEN CARDIORESPIRATORY FITNESS AND ALL-CAUSE MORTALITY: THE FIT (HENRY FORD EXERCISE TESTING) PROJECT. Journal of the American College of Cardiology. 69(11). 1612–1612. 2 indexed citations
14.
Qureshi, Waqas, et al.. (2016). The impact of digoxin on mortality in patients with chronic systolic heart failure: A propensity-matched cohort study. International Journal of Cardiology. 228. 214–218. 14 indexed citations
15.
Batarfi, Omar, Radwa Elshawi, Ayman G. Fayoumi, Ahmed Barnawi, & Sherif Sakr. (2016). A distributed query execution engine of big attributed graphs. SpringerPlus. 5(1). 665–665. 1 indexed citations
16.
Bajaber, Fuad, Radwa Elshawi, Omar Batarfi, et al.. (2016). Big Data 2.0 Processing Systems: Taxonomy and Open Challenges. Journal of Grid Computing. 14(3). 379–405. 35 indexed citations
17.
Barnawi, Ahmed, Ahmed Awad, Amal Elgammal, et al.. (2016). An Anti-Pattern-based Runtime Business Process Compliance Monitoring Framework. International Journal of Advanced Computer Science and Applications. 7(2). 7 indexed citations
18.
Elshawi, Radwa & Sherif Sakr. (2016). International conferences on computer system: Analysis of EuroSys, SOSP, and OSDI during 2006-2014. Collnet Journal of Scientometrics and Information Management. 10(1). 175–195. 1 indexed citations
19.
Sakr, Sherif, Fuad Bajaber, Ahmed Barnawi, et al.. (2015). Big Data Processing Systems: State-of-the-Art and Open Challenges. 1–8. 7 indexed citations
20.
Elshawi, Radwa, Omar Batarfi, Ayman G. Fayoumi, Ahmed Barnawi, & Sherif Sakr. (2015). Big Graph Processing Systems: State-of-the-Art and Open Challenges. 24–33. 6 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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