Nesma Settouti

507 total citations
38 papers, 341 citations indexed

About

Nesma Settouti is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Health Information Management. According to data from OpenAlex, Nesma Settouti has authored 38 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 7 papers in Health Information Management. Recurrent topics in Nesma Settouti's work include Digital Imaging for Blood Diseases (9 papers), AI in cancer detection (7 papers) and Machine Learning and Data Classification (7 papers). Nesma Settouti is often cited by papers focused on Digital Imaging for Blood Diseases (9 papers), AI in cancer detection (7 papers) and Machine Learning and Data Classification (7 papers). Nesma Settouti collaborates with scholars based in Algeria, France and Belgium. Nesma Settouti's co-authors include Mohammed Amine Chikh, Mostafa El Habib Daho, Vincent Barra, Imane Nedjar, Saïd Mahmoudi, Mouloud Adel, Jesse Read, Nathalie Douet‐Guilbert, Samira Khoulji and Chafiaâ Hamitouche and has published in prestigious journals such as Applied Spectroscopy, Journal of Medical Systems and The Computer Journal.

In The Last Decade

Nesma Settouti

34 papers receiving 319 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nesma Settouti Algeria 10 177 82 77 59 45 38 341
Nabiha Azizi Algeria 11 235 1.3× 103 1.3× 28 0.4× 91 1.5× 45 1.0× 47 356
Mohamed Yaseen Jabarulla South Korea 10 86 0.5× 103 1.3× 32 0.4× 93 1.6× 100 2.2× 18 365
Jyothisha J. Nair India 11 131 0.7× 72 0.9× 34 0.4× 59 1.0× 32 0.7× 49 304
Debendra Muduli India 7 250 1.4× 106 1.3× 34 0.4× 171 2.9× 30 0.7× 44 396
Debanjan Konar India 11 221 1.2× 77 0.9× 20 0.3× 75 1.3× 51 1.1× 31 433
Eswaran Perumal India 11 235 1.3× 95 1.2× 127 1.6× 215 3.6× 87 1.9× 36 525
Awais Mehmood Pakistan 9 195 1.1× 225 2.7× 114 1.5× 158 2.7× 27 0.6× 23 549
Rekha Singh India 14 170 1.0× 116 1.4× 62 0.8× 182 3.1× 8 0.2× 20 418
Sania Anam Pakistan 6 77 0.4× 37 0.5× 19 0.2× 81 1.4× 11 0.2× 19 345
Apeksha Koul India 11 189 1.1× 78 1.0× 83 1.1× 76 1.3× 24 0.5× 20 436

Countries citing papers authored by Nesma Settouti

Since Specialization
Citations

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

Fields of papers citing papers by Nesma Settouti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nesma Settouti

This figure shows the co-authorship network connecting the top 25 collaborators of Nesma Settouti. A scholar is included among the top collaborators of Nesma Settouti 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 Nesma Settouti. Nesma Settouti 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.
Settouti, Nesma, et al.. (2025). Exploring Band Selection Methods for Enhanced Chromosomal Analysis in Hyperspectral Imaging. Applied Spectroscopy. 80(2). 133–145.
2.
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Settouti, Nesma, et al.. (2023). Preliminary analysis of explainable machine learning methods for multiple myeloma chemotherapy treatment recognition. Evolutionary Intelligence. 17(1). 513–533. 8 indexed citations
4.
Daho, Mostafa El Habib, et al.. (2021). A new correlation-based approach for ensemble selection in random forests. International Journal of Intelligent Computing and Cybernetics. 14(2). 251–268. 9 indexed citations
5.
Settouti, Nesma, et al.. (2021). Analysis of Machine Learning and Deep Learning Frameworks for Opinion Mining on Drug Reviews. The Computer Journal. 65(9). 2470–2483. 9 indexed citations
6.
Settouti, Nesma, et al.. (2021). A comparison of U-net backbone architectures for the automatic white blood cells segmentation. 4(1). 6 indexed citations
7.
Settouti, Nesma, et al.. (2021). Content Based COVID-19 Chest X-Ray and CT Images Retrieval framework using Stacked Auto-Encoders. 119–124. 6 indexed citations
8.
Settouti, Nesma, et al.. (2020). An optimised pixel-based classification approach for automatic white blood cells segmentation. International Journal of Biomedical Engineering and Technology. 32(2). 144–144. 7 indexed citations
9.
Settouti, Nesma, et al.. (2019). Influence of normalization and color features on super-pixel classification: application to cytological image segmentation. Australasian Physical & Engineering Sciences in Medicine. 42(2). 427–441. 5 indexed citations
10.
11.
Settouti, Nesma, et al.. (2018). An analysis of ambulatory blood pressure monitoring using multi-label classification. Australasian Physical & Engineering Sciences in Medicine. 42(1). 65–81. 6 indexed citations
12.
Daho, Mostafa El Habib, et al.. (2018). Comparaison of Ensemble Cost Sensitive Algorithms: Application to Credit Scoring Prediction.. 56–61. 2 indexed citations
13.
Nedjar, Imane, et al.. (2015). RANDOM FOREST BASED CLASSIFICATION OF MEDICAL X-RAY IMAGES USING A GENETIC ALGORITHM FOR FEATURE SELECTION. Journal of Mechanics in Medicine and Biology. 15(2). 1540025–1540025. 15 indexed citations
14.
Settouti, Nesma, et al.. (2015). A new feature selection approach based on ensemble methods in semi-supervised classification. Pattern Analysis and Applications. 20(3). 673–686. 8 indexed citations
15.
Settouti, Nesma, et al.. (2014). An SVM intelligent system for pre-anesthetic examination. 36. 73–78. 1 indexed citations
16.
Daho, Mostafa El Habib, et al.. (2013). Recognition of diabetes disease using a new hybrid learning algorithm for NEFCLASS. 239–243. 9 indexed citations
17.
Settouti, Nesma, et al.. (2012). Generating fuzzy rules for constructing interpretable classifier of diabetes disease. Australasian Physical & Engineering Sciences in Medicine. 35(3). 257–270. 9 indexed citations
18.
Chikh, Mohammed Amine, et al.. (2011). Automatic Identification of Diabetes Diseases using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-Nearest Neighbor.. 6 indexed citations
19.
Settouti, Nesma, et al.. (2011). Evolving neural networks using a genetic algorithm for heartbeat classification. Journal of Medical Engineering & Technology. 35(5). 215–223. 3 indexed citations
20.
Settouti, Nesma, et al.. (2011). Diagnosis of Diabetes Diseases Using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-nearest Neighbor. Journal of Medical Systems. 36(5). 2721–2729. 83 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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2026