Karim Gasmi

555 total citations
34 papers, 345 citations indexed

About

Karim Gasmi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Neurology. According to data from OpenAlex, Karim Gasmi has authored 34 papers receiving a total of 345 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 5 papers in Neurology. Recurrent topics in Karim Gasmi's work include Image Retrieval and Classification Techniques (6 papers), Brain Tumor Detection and Classification (5 papers) and Artificial Intelligence in Healthcare (4 papers). Karim Gasmi is often cited by papers focused on Image Retrieval and Classification Techniques (6 papers), Brain Tumor Detection and Classification (5 papers) and Artificial Intelligence in Healthcare (4 papers). Karim Gasmi collaborates with scholars based in Saudi Arabia, Tunisia and France. Karim Gasmi's co-authors include Lassaad Ben Ammar, Moez Krichen, Hamoud Alshammari, Mahmood A. Mahmood, Ahmed Kharrat, Nacéra Benamrane, Mohamed Abid, Hanen Karamti, Abdallah Ghourabi and Mariya Ouaissa and has published in prestigious journals such as IEEE Access, Computers and Electronics in Agriculture and Applied Sciences.

In The Last Decade

Karim Gasmi

30 papers receiving 328 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Karim Gasmi Saudi Arabia 11 119 92 74 72 57 34 345
Amena Mahmoud Egypt 11 151 1.3× 76 0.8× 32 0.4× 77 1.1× 53 0.9× 27 340
Venkatramaphanikumar Sistla India 10 122 1.0× 74 0.8× 181 2.4× 30 0.4× 31 0.5× 34 450
Lassaad Ben Ammar Saudi Arabia 8 66 0.6× 45 0.5× 68 0.9× 57 0.8× 25 0.4× 32 273
Ritesh Maurya India 11 142 1.2× 58 0.6× 41 0.6× 52 0.7× 24 0.4× 37 337
G. R. Sreekanth India 9 47 0.4× 47 0.5× 79 1.1× 24 0.3× 40 0.7× 23 245
Yehualashet Megersa Ayano Ethiopia 8 73 0.6× 87 0.9× 34 0.5× 50 0.7× 93 1.6× 10 279
R. Cristin India 9 88 0.7× 79 0.9× 62 0.8× 16 0.2× 35 0.6× 31 279
Syed Inthiyaz India 9 71 0.6× 63 0.7× 55 0.7× 27 0.4× 24 0.4× 41 303
Osama R. Shahin Saudi Arabia 11 87 0.7× 36 0.4× 35 0.5× 54 0.8× 15 0.3× 31 270
Hareem Kibriya Pakistan 10 116 1.0× 138 1.5× 83 1.1× 43 0.6× 136 2.4× 15 337

Countries citing papers authored by Karim Gasmi

Since Specialization
Citations

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

Fields of papers citing papers by Karim Gasmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karim Gasmi

This figure shows the co-authorship network connecting the top 25 collaborators of Karim Gasmi. A scholar is included among the top collaborators of Karim Gasmi 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 Karim Gasmi. Karim Gasmi 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.
Gasmi, Karim, et al.. (2025). Hybrid Feature and Optimized Deep Learning Model Fusion for Detecting Hateful Arabic Content. IEEE Access. 13. 131411–131431. 1 indexed citations
2.
Gasmi, Karim, Adel Alkhalil, Ibrahim Alrashdi, et al.. (2025). Federated and ensemble learning framework with optimized feature selection for heart disease detection. AIMS Mathematics. 10(3). 7290–7318. 1 indexed citations
3.
Gasmi, Karim, et al.. (2025). Enhanced Multimodal Physiological Signal Analysis for Pain Assessment Using Optimized Ensemble Deep Learning. Computer Modeling in Engineering & Sciences. 143(2). 2459–2489. 1 indexed citations
4.
Gasmi, Karim, et al.. (2024). Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique. Frontiers in Neuroinformatics. 18. 1444650–1444650. 5 indexed citations
5.
Gasmi, Karim, et al.. (2024). Optimal Ensemble Learning Model for Dyslexia Prediction Based on an Adaptive Genetic Algorithm. IEEE Access. 12. 64754–64764. 7 indexed citations
6.
Gasmi, Karim, et al.. (2024). Optimized Hybrid Deep Learning Framework for Early Detection of Alzheimer’s Disease Using Adaptive Weight Selection. Diagnostics. 14(24). 2779–2779. 5 indexed citations
7.
Gasmi, Karim, et al.. (2024). Enhancing Medical Image Retrieval with UMLS-Integrated CNN-Based Text Indexing. Diagnostics. 14(11). 1204–1204. 1 indexed citations
8.
Gasmi, Karim, et al.. (2024). An Optimal Model for Medical Text Classification Based on Adaptive Genetic Algorithm. Data Science and Engineering. 9(4). 378–392. 3 indexed citations
9.
Gasmi, Karim, Ahmed Kharrat, Lassaad Ben Ammar, et al.. (2024). Classification of MRI brain tumors based on registration preprocessing and deep belief networks. AIMS Mathematics. 9(2). 4604–4631. 4 indexed citations
10.
Gasmi, Karim, et al.. (2023). Link-Driven Study to Enhance Text-Based Image Retrieval: Implicit Links Versus Explicit Links. IEEE Access. 11. 90526–90537. 1 indexed citations
11.
Mahmood, Mahmood A., et al.. (2023). A Granular Computing Classifier for Human Activity with Smartphones. Applied Sciences. 13(2). 1175–1175. 1 indexed citations
12.
Gasmi, Karim. (2022). Hybrid deep learning model for answering visual medical questions. The Journal of Supercomputing. 78(13). 15042–15059. 10 indexed citations
13.
Gasmi, Karim, et al.. (2022). SolarRadnet: A novel variant input scoring optimized recurrent neural network for solar irradiance prediction. Energy Sources Part A Recovery Utilization and Environmental Effects. 44(4). 10156–10180. 1 indexed citations
14.
Alshammari, Hamoud, et al.. (2022). Choosing the best quality of service algorithm using OPNET simulation. International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering. 12(4). 4079–4079.
15.
Gasmi, Karim, Hamoud Alshammari, Hanen Karamti, et al.. (2022). Tuberculosis Disease Diagnosis Based on an Optimized Machine Learning Model. Journal of Healthcare Engineering. 2022. 1–13. 52 indexed citations
16.
Mahmood, Mahmood A., et al.. (2021). A Hybrid Clustering Technique to Propose the Countries for HELP International. Indian Journal of Computer Science and Engineering. 12(1). 306–314. 2 indexed citations
17.
Gasmi, Karim, et al.. (2019). Document/query expansion based on selecting significant concepts for context based retrieval of medical images. Journal of Biomedical Informatics. 95. 103210–103210. 20 indexed citations
18.
Gasmi, Karim, et al.. (2012). Word Indexing Versus Conceptual Indexing in Medical Image Retrieval..
19.
Kharrat, Ahmed, et al.. (2011). Medical Image Classification Using an Optimal Feature Extraction Algorithm and a Supervised Classifier Technique. International Journal of Software Science and Computational Intelligence. 3(2). 19–33. 14 indexed citations
20.

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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