Nour Eldeen M. Khalifa

3.6k total citations · 4 hit papers
33 papers, 2.0k citations indexed

About

Nour Eldeen M. Khalifa is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nour Eldeen M. Khalifa has authored 33 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 11 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nour Eldeen M. Khalifa's work include COVID-19 diagnosis using AI (10 papers), AI in cancer detection (6 papers) and Face recognition and analysis (3 papers). Nour Eldeen M. Khalifa is often cited by papers focused on COVID-19 diagnosis using AI (10 papers), AI in cancer detection (6 papers) and Face recognition and analysis (3 papers). Nour Eldeen M. Khalifa collaborates with scholars based in Egypt, United States and Taiwan. Nour Eldeen M. Khalifa's co-authors include Mohamed Loey, Mohamed Hamed N. Taha, Gunasekaran Manogaran, Florentín Smarandache, Seyedali Mirjalili, Aboul Ella Hassanien, Dalia Ezzat, Adam Słowik, Roheet Bhatnagar and Hazem M. El‐Bakry and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

In The Last Decade

Nour Eldeen M. Khalifa

30 papers receiving 2.0k citations

Hit Papers

4 papers align trajectories

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.

A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic

2020 457 citations Mohamed Loey, Gunasekaran Manogaran et al. Measurement profile →
Within the Lack of Chest COVID-19 X-ray Dataset: A Novel Detection Model Based on GAN and Deep Transfer Learning

2020 385 citations Mohamed Loey, Florentín Smarandache et al. Symmetry profile →
Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection

2020 322 citations Mohamed Loey, Gunasekaran Manogaran et al. Sustainable Cities and Society profile →
A comprehensive survey of recent trends in deep learning for digital images augmentation

2021 235 citations Nour Eldeen M. Khalifa, Mohamed Loey et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nour Eldeen M. Khalifa Egypt	16	1.0k	817	699	203	149	33	2.0k
Mohamed Loey Egypt	14	1.1k 1.1×	953 1.2×	793 1.1×	238 1.2×	151 1.0×	24	2.2k
Burhan Ergen Türkiye	25	1.1k 1.1×	878 1.1×	1.2k 1.7×	222 1.1×	89 0.6×	90	2.6k
Tanveer Syeda-Mahmood United States	24	700 0.7×	946 1.2×	688 1.0×	190 0.9×	193 1.3×	143	2.4k
Mugahed A. Al–antari South Korea	24	1.1k 1.1×	508 0.6×	1.6k 2.3×	189 0.9×	107 0.7×	94	2.5k
Mesut Toğaçar Türkiye	22	1.2k 1.2×	761 0.9×	1.2k 1.7×	188 0.9×	91 0.6×	57	2.3k
Mohammed Elmogy Egypt	26	910 0.9×	817 1.0×	768 1.1×	160 0.8×	39 0.3×	169	2.5k
Idit Diamant Israel	11	752 0.7×	686 0.8×	868 1.2×	152 0.7×	76 0.5×	19	1.9k
Zafer Cömert Türkiye	31	1.4k 1.4×	858 1.1×	1.5k 2.2×	459 2.3×	138 0.9×	78	3.5k
P. K. Gupta India	14	806 0.8×	255 0.3×	660 0.9×	146 0.7×	156 1.0×	94	1.7k
Bin Sheng China	24	611 0.6×	1.0k 1.3×	348 0.5×	153 0.8×	29 0.2×	114	2.1k

Countries citing papers authored by Nour Eldeen M. Khalifa

Since Specialization

Citations

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

Fields of papers citing papers by Nour Eldeen M. Khalifa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nour Eldeen M. Khalifa. 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 Nour Eldeen M. Khalifa. The network helps show where Nour Eldeen M. Khalifa may publish in the future.

Co-authorship network of co-authors of Nour Eldeen M. Khalifa

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Khalifa, Nour Eldeen M., et al.. (2025). A survey on resource scheduling approaches in multi-access edge computing environment: a deep reinforcement learning study. Cluster Computing. 28(3). 9 indexed citations

Taha, Mohamed Hamed N., et al.. (2025). Enhancing Data Privacy and Trust in E‐Learning: A Blockchain‐Based Access Control Protocol for Cloud Educational Systems. Concurrency and Computation Practice and Experience. 37(18-20).

Khalifa, Nour Eldeen M., et al.. (2024). COECG-resnet-GWO-SVM: an optimized COVID-19 electrocardiography classification model based on resnet50, grey wolf optimization and support vector machine. Multimedia Tools and Applications. 84(17). 18305–18325. 1 indexed citations

Khalifa, Nour Eldeen M., et al.. (2023). A Model based on Deep Learning for COVID-19 X-rays Classification. International Journal of Image Graphics and Signal Processing. 15(1). 36–46. 2 indexed citations

Khalifa, Nour Eldeen M., et al.. (2023). Cyber-Physical Systems for Industrial Transformation. 2 indexed citations

Khalifa, Nour Eldeen M., et al.. (2023). A COVID-19 Infection Prediction Model in Egypt Based on Deep Learning Using Population Mobility Reports. International Journal of Computational Intelligence Systems. 16(1). 2 indexed citations

Khalifa, Nour Eldeen M., et al.. (2021). The classification of possible Coronavirus treatments on a single human cell using deep learning and machine learning approaches. Figshare. 1 indexed citations

Khalifa, Nour Eldeen M., Gunasekaran Manogaran, Mohamed Hamed N. Taha, & Mohamed Loey. (2021). A deep learning semantic segmentation architecture for COVID‐19 lesions discovery in limited chest CT datasets. Expert Systems. 39(6). e12742–e12742. 17 indexed citations

Khalifa, Nour Eldeen M., Florentín Smarandache, Gunasekaran Manogaran, & Mohamed Loey. (2021). A Study of the Neutrosophic Set Significance on Deep Transfer Learning Models: an Experimental Case on a Limited COVID-19 Chest X-ray Dataset. Cognitive Computation. 16(4). 1602–1611. 33 indexed citations

10.

Hassanien, Aboul Ella, Mohamed Hamed N. Taha, & Nour Eldeen M. Khalifa. (2020). Enabling AI Applications in Data Science. Studies in computational intelligence. 18 indexed citations

11.

Loey, Mohamed, Florentín Smarandache, & Nour Eldeen M. Khalifa. (2020). Within the Lack of Chest COVID-19 X-ray Dataset: A Novel Detection Model Based on GAN and Deep Transfer Learning. Symmetry. 12(4). 651–651. 385 indexed citations breakdown →

12.

Loey, Mohamed, Gunasekaran Manogaran, Mohamed Hamed N. Taha, & Nour Eldeen M. Khalifa. (2020). A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic. Measurement. 167. 108288–108288. 457 indexed citations breakdown →

13.

Soliman, Mona, et al.. (2020). Automatic Classification of Retinal Eye Diseases from Optical Coherence Tomography using Transfer Learning. 37–42. 17 indexed citations

14.

Loey, Mohamed, Gunasekaran Manogaran, Mohamed Hamed N. Taha, & Nour Eldeen M. Khalifa. (2020). Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection. Sustainable Cities and Society. 65. 102600–102600. 322 indexed citations breakdown →

15.

Hassanien, Aboul Ella, Roheet Bhatnagar, Nour Eldeen M. Khalifa, & Mohamed Hamed N. Taha. (2019). Toward Social Internet of Things (SIoT): Enabling Technologies, Architectures and Applications. Studies in computational intelligence. 39 indexed citations

16.

Khalifa, Nour Eldeen M., et al.. (2019). Deep Transfer Learning Models for Medical Diabetic Retinopathy Detection. Acta Informatica Medica. 27(5). 327–327. 91 indexed citations

17.

Khalifa, Nour Eldeen M., et al.. (2019). Deep Iris: Deep Learning for Gender Classification Through Iris Patterns. Acta Informatica Medica. 27(2). 96–96. 23 indexed citations

18.

Kotb, Magd A., et al.. (2015). Pediatric Online Evidence-Based Medicine Assignment Is a Novel Effective Enjoyable Undergraduate Medical Teaching Tool. Medicine. 94(29). e1178–e1178. 2 indexed citations

19.

Khalifa, Nour Eldeen M., Mohamed Hamed N. Taha, Hesham N. Elmahdy, & Imane Aly Saroit. (2013). A Secure Energy Efficient Schema for Wireless Multimedia Sensor Networks. 5(6). 235–245. 2 indexed citations

20.

Khalifa, Nour Eldeen M., Mohamed Hamed N. Taha, Hesham N. Elmahdy, & Imane Aly Saroit. (2012). A Secure Energy Mechanism for WSN and Its Implementation in NS-2. 4(16). 984–990. 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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