Ammar Mohammed

3.2k total citations · 2 hit papers
75 papers, 1.8k citations indexed

About

Ammar Mohammed is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ammar Mohammed has authored 75 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 9 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ammar Mohammed's work include Topic Modeling (16 papers), Advanced Text Analysis Techniques (10 papers) and Sentiment Analysis and Opinion Mining (8 papers). Ammar Mohammed is often cited by papers focused on Topic Modeling (16 papers), Advanced Text Analysis Techniques (10 papers) and Sentiment Analysis and Opinion Mining (8 papers). Ammar Mohammed collaborates with scholars based in Egypt, United States and Saudi Arabia. Ammar Mohammed's co-authors include Rania Kora, Hesham A. Hefny, Eslam Amer, Jagadeesh Pasupuleti, Usman Tariq, Ahmed Elmogy, Atef Ibrahim, Wilfried Elmenreich, Tamer Khatib and Lamiaa Fattouh Ibrahim and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Scientific Reports.

In The Last Decade

Ammar Mohammed

61 papers receiving 1.7k citations

Hit Papers

A comprehensive review on ensemble d... 2019 2026 2021 2023 2023 2019 100 200 300 400 500
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.

  1. A comprehensive review on ensemble deep learning: Opportunities and challenges
    2023 527 citations Ammar Mohammed et al. Journal of King Saud University - Computer and Information Sciences profile →
  2. An enhanced deep learning approach for brain cancer MRI images classification using residual networks
    2019 289 citations Ammar Mohammed, Hesham A. Hefny et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ammar Mohammed Egypt 19 863 324 252 243 168 75 1.8k
Muhammad Usman Ghani Khan Pakistan 23 781 0.9× 592 1.8× 256 1.0× 281 1.2× 175 1.0× 112 2.0k
Shakir Khan Saudi Arabia 21 457 0.5× 255 0.8× 200 0.8× 210 0.9× 171 1.0× 81 1.3k
Shtwai Alsubai Saudi Arabia 20 504 0.6× 354 1.1× 240 1.0× 183 0.8× 96 0.6× 182 1.5k
Gaurav Gupta India 19 376 0.4× 252 0.8× 224 0.9× 182 0.7× 139 0.8× 88 1.4k
Jyotir Moy Chatterjee India 19 590 0.7× 279 0.9× 430 1.7× 214 0.9× 221 1.3× 68 2.2k
Adi Alhudhaif Saudi Arabia 27 630 0.7× 513 1.6× 242 1.0× 152 0.6× 126 0.8× 106 2.0k
M. F. Mridha Bangladesh 27 1.1k 1.3× 413 1.3× 236 0.9× 135 0.6× 302 1.8× 243 2.7k
Saroj Kr. Biswas India 19 756 0.9× 267 0.8× 274 1.1× 75 0.3× 155 0.9× 108 1.6k
Chastine Fatichah Indonesia 23 709 0.8× 512 1.6× 227 0.9× 124 0.5× 386 2.3× 306 1.9k
Hamid Tairi Morocco 20 393 0.5× 721 2.2× 172 0.7× 165 0.7× 144 0.9× 170 1.4k

Countries citing papers authored by Ammar Mohammed

Since Specialization
Citations

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

Fields of papers citing papers by Ammar Mohammed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ammar Mohammed

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

All Works

20 of 20 papers shown
1.
Allam, Anirudh, et al.. (2025). Arabic Large Language Models for Medical Text Generation. 1–6. 1 indexed citations
2.
Mohammed, Ammar, et al.. (2024). Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques. Scientific Reports. 14(1). 29582–29582. 1 indexed citations
3.
4.
Mohammed, Ammar, et al.. (2024). MRD‐GAN: Multi‐representation discrimination GAN for enhancing the diversity of the generated data. Computational Intelligence. 40(3). 1 indexed citations
5.
Mohammed, Ammar, et al.. (2024). Large language models-based metric for generative question answering systems. IAES International Journal of Artificial Intelligence. 14(1). 151–151. 1 indexed citations
6.
Mohammed, Ammar, et al.. (2023). Deep learning for Arabic healthcare: MedicalBot. Social Network Analysis and Mining. 13(1). 71–71. 29 indexed citations
7.
Mohammed, Ammar, et al.. (2023). A Comprehensive Survey on Arabic Sarcasm Detection: Approaches, Challenges and Future Trends. IEEE Access. 11. 18261–18280. 19 indexed citations
8.
Mohammed, Ammar, et al.. (2023). Deep Learning Approach for Liver Tumor Diagnosis. 11. 210–216. 2 indexed citations
9.
Mohammed, Ammar, et al.. (2023). Detection of Malaria Infection Using Convolutional Neural Networks. 102. 291–296. 1 indexed citations
10.
Mohammed, Ammar, et al.. (2023). A comprehensive review of generative adversarial networks: Fundamentals, applications, and challenges. Wiley Interdisciplinary Reviews Computational Statistics. 16(1). 15 indexed citations
11.
12.
Mahmoud, Ahmed M., et al.. (2023). Integrated Deep Learning Framework for Insect Detection and Classification in Video Streams. 51. 1–6. 3 indexed citations
13.
14.
Mohammed, Ammar, et al.. (2023). Artificial Intelligence Role in Subclassifying Cytology of Thyroid Follicular Neoplasm. Asian Pacific Journal of Cancer Prevention. 24(4). 1379–1387. 30 indexed citations
15.
Mohammed, Ammar, et al.. (2023). An Enhanced Genetic Algorithm using Directional-Based Crossover and normal mutation For Global Optimization Problems. Statistics Optimization & Information Computing. 12(2). 446–462. 2 indexed citations
16.
17.
Mohammed, Ammar, et al.. (2022). A Fuzzy-Crisp Frequent Concept Lattice Generation Algorithm. 75–80. 1 indexed citations
18.
Mohammed, Ammar, et al.. (2021). Improving the Performance of Deep Neural Networks Using Two Proposed Activation Functions. IEEE Access. 9. 82249–82271. 38 indexed citations
19.
Mohammed, Ammar, et al.. (2019). An Enhanced Opinion Retrieval Approach on Arabic Text for Customer Requirements Expansion. Journal of King Saud University - Computer and Information Sciences. 33(3). 351–363. 6 indexed citations
20.
Mohammed, Ammar, et al.. (2015). Using Textual Case-based Reasoning in Intelligent Fatawa QA System. The International Arab Journal of Information Technology. 12(5). 503–509. 13 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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