Mona Jamjoom

2.0k citations
78 papers · 1.2k · h-index 20

Impact in

Papers in

Mona Jamjoom

66 papers receiving 1.1k citations

Peers

Mona Jamjoom
Comparison fields: 5 of 130
  • Neurology 152
  • Computer Science Applications 93
  • Health Information Management 56
  • Artificial Intelligence 398
  • Computer Vision and Pattern Recognition 215
Replace K. Vijayakumar with:
K. Vijayakumar India
Vinit Kumar Gunjan India
Shakir Khan Saudi Arabia
Khan Md. Hasib Bangladesh
Sultan Alfarhood Saudi Arabia
Sunil L. Bangare India
Galip Aydın Türkiye
Brojo Kishore Mishra India
Saad Alanazi Saudi Arabia
Rabia Musheer Aziz India
Mona Jamjoom relative to K. Vijayakumar India K. Vijayakumar's profile →
Citations per field
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K. Vijayakumar · 1×
Citations per year

Countries citing papers authored by Mona Jamjoom

Since Specialization
Citations

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

Fields of papers citing papers by Mona Jamjoom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mona Jamjoom, 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 Mona Jamjoom Line = papers co-authored together Mona Jamjoom links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202292
2 202376
3 202360
4 202356
5 202055
6 201854
7 202253
8 202353
9 202247
10 202340
11 202234
12 202330
13 202129
14 202126
15 201925
16 202422
17 202421
18 202220
19 202320
20 202219

About Mona Jamjoom

Mona Jamjoom is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Radiology, Nuclear Medicine and Imaging and Computer Networks and Communications, having authored 78 papers that have together received 1.2k indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (7 papers), AI in cancer detection (7 papers), Sentiment Analysis and Opinion Mining (6 papers), Brain Tumor Detection and Classification (6 papers), Hate Speech and Cyberbullying Detection (5 papers), Video Surveillance and Tracking Methods (5 papers), Vehicle License Plate Recognition (4 papers) and Topic Modeling (4 papers). The work is most often cited by research in Neurology (152 citations), Computer Science Applications (93 citations), Health Information Management (56 citations), Artificial Intelligence (398 citations) and Computer Vision and Pattern Recognition (215 citations). Mona Jamjoom has collaborated with scholars based in Saudi Arabia, Pakistan and Egypt. Frequent co-authors include Zahid Ullah, Nagwan Abdel Samee, Farrukh Saleem, El‐Sayed M. El‐kenawy, Abdelhameed Ibrahim‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Abdelaziz A. Abdelhamid, Essam H. Houssein, Amel Ksibi, Marwa M. Emam and Muhammad Shahid Iqbal Malik. Their work appears in journals such as IEEE Access, Computers, materials & continua/Computers, materials & continua (Print), Scientific Reports, Computers in Biology and Medicine and PeerJ Computer Science.

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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