George E. Sakr

707 total citations
22 papers, 470 citations indexed

About

George E. Sakr is a scholar working on Cardiology and Cardiovascular Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, George E. Sakr has authored 22 papers receiving a total of 470 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cardiology and Cardiovascular Medicine, 5 papers in Artificial Intelligence and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in George E. Sakr's work include Cardiac Imaging and Diagnostics (3 papers), EEG and Brain-Computer Interfaces (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). George E. Sakr is often cited by papers focused on Cardiac Imaging and Diagnostics (3 papers), EEG and Brain-Computer Interfaces (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). George E. Sakr collaborates with scholars based in Lebanon, United States and France. George E. Sakr's co-authors include Imad H. Elhajj, George Mitri, Ali S. Hadi, Uchechukwu C. Wejinya, Rima Kilany, Chadi Jabbour, Hussain Isma’eel, Wael A. Jaber, Paul Cremer and Shaden Khalaf and has published in prestigious journals such as SHILAP Revista de lepidopterología, Engineering Applications of Artificial Intelligence and European Journal of Clinical Pharmacology.

In The Last Decade

George E. Sakr

20 papers receiving 447 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
George E. Sakr Lebanon 9 107 93 82 65 49 22 470
Raghvendra Kumar India 11 92 0.9× 65 0.7× 69 0.8× 22 0.3× 96 2.0× 31 527
Umi Kalthum Ngah Malaysia 15 95 0.9× 212 2.3× 254 3.1× 78 1.2× 141 2.9× 50 690
Ljiljana Šerić Croatia 10 40 0.4× 79 0.8× 71 0.9× 13 0.2× 7 0.1× 40 357
Taoseef Ishtiak Bangladesh 4 23 0.2× 105 1.1× 50 0.6× 33 0.5× 6 0.1× 7 454
B. S. Sathish India 10 21 0.2× 65 0.7× 198 2.4× 18 0.3× 5 0.1× 33 499
Damir Krstinić Croatia 11 61 0.6× 66 0.7× 172 2.1× 8 0.1× 6 0.1× 26 387
Vatsal Patel India 4 22 0.2× 72 0.8× 25 0.3× 14 0.2× 8 0.2× 9 312
Tobias Pielok Germany 2 21 0.2× 135 1.5× 23 0.3× 14 0.2× 8 0.2× 2 434
Sethuraman N Rao India 15 98 0.9× 75 0.8× 107 1.3× 18 0.3× 6 0.1× 93 751
Zahraa Tarek Egypt 14 16 0.1× 177 1.9× 23 0.3× 47 0.7× 7 0.1× 36 625

Countries citing papers authored by George E. Sakr

Since Specialization
Citations

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

Fields of papers citing papers by George E. Sakr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by George E. Sakr. 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 George E. Sakr. The network helps show where George E. Sakr may publish in the future.

Co-authorship network of co-authors of George E. Sakr

This figure shows the co-authorship network connecting the top 25 collaborators of George E. Sakr. A scholar is included among the top collaborators of George E. Sakr 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 George E. Sakr. George E. Sakr 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.
2.
Jabbour, Chadi, et al.. (2022). A Review of Machine Learning Techniques in Analog Integrated Circuit Design Automation. Electronics. 11(3). 435–435. 40 indexed citations
3.
Shammas, Elie, et al.. (2022). Semantic Segmentation of Maxillary Teeth and Palatal Rugae in Two-Dimensional Images. Diagnostics. 12(9). 2176–2176. 9 indexed citations
4.
5.
Abdulrahim, Sawsan, et al.. (2021). Integration of Palestinian Refugee Children from Syria in UNRWA Schools in Lebanon. Journal of International Migration and Integration / Revue de l integration et de la migration internationale. 22(4). 1207–1219. 4 indexed citations
6.
Sakr, George E., et al.. (2020). Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19. Machine Vision and Applications. 31(6). 53–53. 52 indexed citations
7.
Sakr, George E., et al.. (2019). Convolution Neural Networks for Arabic Font Recognition. 23. 128–133. 4 indexed citations
8.
Walsh, Jason, Wael AlJaroudi, Ossama Abou Hassan, et al.. (2019). A speckle-tracking strain-based artificial neural network model to differentiate cardiomyopathy type. Scandinavian Cardiovascular Journal. 54(2). 92–99. 4 indexed citations
9.
Isma’eel, Hussain, George E. Sakr, Paul Cremer, et al.. (2017). Artificial neural network-based model enhances risk stratification and reduces non-invasive cardiac stress imaging compared to Diamond–Forrester and Morise risk assessment models: A prospective study. Journal of Nuclear Cardiology. 25(5). 1601–1609. 6 indexed citations
10.
Sakr, George E., et al.. (2016). Intensive Lipid Lowering Therapy among patients with Coronary Artery Disease: a Middle Eastern tertiary care center experience. SHILAP Revista de lepidopterología. 6. 2 indexed citations
11.
Isma’eel, Hussain, Paul Cremer, Shaden Khalaf, et al.. (2015). Artificial neural network modeling enhances risk stratification and can reduce downstream testing for patients with suspected acute coronary syndromes, negative cardiac biomarkers, and normal ECGs. International journal of cardiac imaging. 32(4). 687–696. 14 indexed citations
12.
13.
Sakr, George E. & Imad H. Elhajj. (2014). VC-based confidence and credibility for support vector machines. Soft Computing. 20(1). 133–147. 6 indexed citations
14.
Sakr, George E. & Imad H. Elhajj. (2013). Decision confidence-based multi-level support vector machines. Engineering Applications of Artificial Intelligence. 26(8). 1892–1901. 6 indexed citations
15.
Sakr, George E., Imad H. Elhajj, & George Mitri. (2011). Efficient forest fire occurrence prediction for developing countries using two weather parameters. Engineering Applications of Artificial Intelligence. 24(5). 888–894. 74 indexed citations
16.
Sakr, George E. & Imad H. Elhajj. (2011). Digit recognition with confidence. 4. 299–304. 1 indexed citations
17.
Sakr, George E., et al.. (2010). Support Vector Machines to Define and Detect Agitation Transition. IEEE Transactions on Affective Computing. 1(2). 98–108. 43 indexed citations
18.
Sakr, George E., Imad H. Elhajj, George Mitri, & Uchechukwu C. Wejinya. (2010). Artificial intelligence for forest fire prediction. 1311–1316. 63 indexed citations
19.
Sakr, George E., Imad H. Elhajj, & Uchechukwu C. Wejinya. (2009). Multi level SVM for subject independent agitation detection. 123. 538–543. 8 indexed citations
20.
Sakr, George E., et al.. (2008). Subject independent agitation detection. 200–204. 5 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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