Mohamed Ezz

39 papers receiving 408 citations

Peers

Mohamed Ezz
Comparison fields: 5 of 98
  • Health Information Management 47
  • Computer Science Applications 46
  • Artificial Intelligence 159
  • Hepatology 35
  • Information Systems 97
Replace Majid Zaman with:
Majid Zaman India
Muhammad Arif Shah Pakistan
Mansur Alp Toçoğlu Türkiye
O‐Joun Lee South Korea
Aina Musdholifah Indonesia
Ramjeevan Singh Thakur India
Mohamed Reda Bouadjenek Australia
Faris Kateb Saudi Arabia
Hyuk-Yoon Kwon South Korea
Parminder Kaur India
Mohamed Ezz relative to Majid Zaman India Majid Zaman's profile →
Citations per field
00.5×8.8×
Majid Zaman · 1×
Citations per year

Countries citing papers authored by Mohamed Ezz

Since Specialization
Citations

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

Fields of papers citing papers by Mohamed Ezz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mohamed Ezz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mohamed Ezz Line = papers co-authored together Mohamed Ezz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201951
2 201949
3 202037
4 201935
5 200835
6 202325
7 201625
8 202322
9 202318
10 202314
11 202313
12 202113
13 202012
14 202212
15 202011
16 20239
17 20246
18 20255
19 20235
20 20205

About Mohamed Ezz

Mohamed Ezz is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Epidemiology, having authored 47 papers that have together received 447 indexed citations. Recurring topics across this work include Biometric Identification and Security (6 papers), AI in cancer detection (6 papers), Face recognition and analysis (5 papers), User Authentication and Security Systems (5 papers), Text and Document Classification Technologies (4 papers), Network Security and Intrusion Detection (4 papers), Liver Disease Diagnosis and Treatment (4 papers) and Brain Tumor Detection and Classification (3 papers). The work is most often cited by research in Health Information Management (47 citations), Computer Science Applications (46 citations), Artificial Intelligence (159 citations), Hepatology (35 citations) and Information Systems (97 citations). Mohamed Ezz has collaborated with scholars based in Saudi Arabia, Egypt and South Africa. Frequent co-authors include Hany Harb, Murtada K. Elbashir, Mohanad Mohammed, Meshrif Alruily, Saleh Naif Almuayqil, Amjad Alsirhani, Mahmoud ElHefnawi, Wafaa Elakel, Wael Said and Mohammed Shokr. Their work appears in journals such as Applied Sciences, IEEE Access, International Journal of Intelligent Systems, Electronics and Computers, materials & continua/Computers, materials & continua (Print).

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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