T. Medhat

19 papers receiving 335 citations

Peers

T. Medhat
Comparison fields: 5 of 63
  • Computational Theory and Mathematics 227
  • Management Science and Operations Research 70
  • Information Systems 93
  • Health Information Management 16
  • Signal Processing 33
Replace Ahmed Mostafa Khalil with:
Ahmed Mostafa Khalil Egypt
Ion Iancu Romania
Beata Zielosko Poland
Robert Nowicki Poland
Pedro Barahona Portugal
Daan Fierens Belgium
Iwan Tri Riyadi Yanto Indonesia
Peter Brockhausen Germany
Silvia Acid Spain
T. Medhat relative to Ahmed Mostafa Khalil Egypt Ahmed Mostafa Khalil's profile →
Citations per field
00.5×10×14×
Ahmed Mostafa Khalil · 1×
Citations per year

Countries citing papers authored by T. Medhat

Since Specialization
Citations

This map shows the geographic impact of T. Medhat'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 T. Medhat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Medhat more than expected).

Fields of papers citing papers by T. Medhat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2005193
2 202341
3 200531
4 202322
5 202218
6 202518
7 20125
8 20234
9 20174
10 20124
11 20213
12 20113
13 20222
14 20251
15 20251
16 20251
17 20201
18
The Relation Between Rough Sets And Fuzzy Sets Via Topological Spaces
20181
19 20221
20 20220

About T. Medhat

T. Medhat is a scholar working on Computational Theory and Mathematics, Information Systems, Artificial Intelligence, Signal Processing and Radiology, Nuclear Medicine and Imaging, having authored 20 papers that have together received 354 indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (10 papers), Data Mining Algorithms and Applications (7 papers), Data Management and Algorithms (4 papers), Brain Tumor Detection and Classification (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), AI in cancer detection (2 papers), Cognitive Computing and Networks (1 paper) and Advanced Database Systems and Queries (1 paper). The work is most often cited by research in Computational Theory and Mathematics (227 citations), Management Science and Operations Research (70 citations), Information Systems (93 citations), Health Information Management (16 citations) and Signal Processing (33 citations). T. Medhat has collaborated with scholars based in Egypt, Saudi Arabia and Romania. Frequent co-authors include A.M. Kozae, Anmar Khadra, M. Z. Rashad, Ali I. Siam, Abeer Saber, Amr A. Abohany, Kumudu S. Munasinghe, Ahmed Sedik, Esraa Hassan and Karam M. Sallam. Their work appears in journals such as Expert Systems with Applications, INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences, Scientific African, Complexity and International Journal of Approximate Reasoning.

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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