Mohammad Nassef

872 citations
20 papers · 573 · h-index 7

Impact in

Papers in

    • Algorithms and Data Compression 3
    • Neural Networks and Applications 2
    • Evolutionary Algorithms and Applications 2
    • AI in cancer detection 2
    • Gene expression and cancer classification 5
    • Machine Learning in Bioinformatics 4

Mohammad Nassef

18 papers receiving 552 citations

Peers

Mohammad Nassef
Comparison fields: 5 of 102
  • Health Informatics 14
  • Artificial Intelligence 298
  • Radiology, Nuclear Medicine and Imaging 161
  • Computer Science Applications 26
  • Health Information Management 19
Replace Saeed Iqbal with:
Saeed Iqbal Pakistan
Mohammed Meknassi Morocco
Shivam Kalra Canada
Woong-Kee Loh South Korea
Kaniz Fatema Bangladesh
Parminder Kaur India
Naveed Abbas Pakistan
Vasundhara Acharya India
Abdulkareem Alzahrani Saudi Arabia
Yan Qiang China
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Citations per field
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Citations per year

Countries citing papers authored by Mohammad Nassef

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Nassef

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 6 scholars most cited alongside Mohammad Nassef, 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 Mohammad Nassef Line = papers co-authored together Mohammad Nassef links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2017204
2 2018161
3 201993
4 201827
5 201627
6 202020
7 20186
8 20195
9 20194
10 20174
11 20164
12 20163
13 20233
14 20193
15 20173
16 20212
17 20192
18 20042
19 20250
20 20140

About Mohammad Nassef

Mohammad Nassef is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 573 indexed citations. Recurring topics across this work include Gene expression and cancer classification (5 papers), Machine Learning in Bioinformatics (4 papers), Algorithms and Data Compression (3 papers), Neural Networks and Applications (2 papers), Evolutionary Algorithms and Applications (2 papers), AI in cancer detection (2 papers), Software Engineering Research (2 papers) and Advanced Control Systems Design (2 papers). The work is most often cited by research in Health Informatics (14 citations), Artificial Intelligence (298 citations), Radiology, Nuclear Medicine and Imaging (161 citations), Computer Science Applications (26 citations) and Health Information Management (19 citations). Mohammad Nassef has collaborated with scholars based in Egypt and Saudi Arabia. Frequent co-authors include Ibrahim Farag, Amr Badr, Hesham Hassan, Hesham A. Hefny, Ahmed H. Madian and Monagi H. Alkinani. Their work appears in journals such as IEEE Access, Computer Methods and Programs in Biomedicine, PeerJ Computer Science, Expert Systems with Applications and Soft Computing.

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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