Halima Bensmail

3.1k citations
97 papers · 2.2k · h-index 28

Impact in

Papers in

    • Gene expression and cancer classification 14
    • Bioinformatics and Genomic Networks 13
    • Machine Learning in Bioinformatics 8
    • Bayesian Methods and Mixture Models 8
    • Advanced Clustering Algorithms Research 7

Halima Bensmail

92 papers receiving 2.1k citations

Peers

Halima Bensmail
Comparison fields: 5 of 175
  • Computer Vision and Pattern Recognition 373
  • Artificial Intelligence 522
  • Statistics and Probability 119
  • Industrial and Manufacturing Engineering 118
  • Media Technology 100
Replace Xiaoning Qian with:
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Malik Yousef Israel
Slobodan Vučetić United States
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Sivaraman Balakrishnan United States
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Mehmet Gönen Türkiye
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Citations per field
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Citations per year

Countries citing papers authored by Halima Bensmail

Since Specialization
Citations

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

Fields of papers citing papers by Halima Bensmail

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 97 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018161
2 1997152
3 1996142
4 2019112
5 2020102
6 201397
7 200695
8 202189
9 200562
10 202061
11 202054
12 201853
13 201352
14 201941
15 199640
16 201837
17 201537
18 201336
19 200535
20 200634

About Halima Bensmail

Halima Bensmail is a scholar working on Molecular Biology, Artificial Intelligence, Computer Vision and Pattern Recognition, Materials Chemistry and Statistics and Probability, having authored 97 papers that have together received 2.2k indexed citations. Recurring topics across this work include Gene expression and cancer classification (14 papers), Bioinformatics and Genomic Networks (13 papers), Bayesian Methods and Mixture Models (8 papers), Machine Learning in Bioinformatics (8 papers), Advanced Clustering Algorithms Research (7 papers), Machine Learning in Materials Science (7 papers), Image Retrieval and Classification Techniques (6 papers) and Advanced Statistical Methods and Models (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (373 citations), Artificial Intelligence (522 citations), Statistics and Probability (119 citations), Industrial and Manufacturing Engineering (118 citations) and Media Technology (100 citations). Halima Bensmail has collaborated with scholars based in Qatar, United States and Italy. Frequent co-authors include Gilles Celeux, Raghvendra Mall, Jim Jing-Yan Wang, Xin Gao, Samir Brahim Belhaouari, Khalid Kunji, Abdelali Haoudi, Reda Rawi, Christian P. Robert and Adrian E. Raftery. Their work appears in journals such as Bioinformatics, BioMed Research International, Journal of Translational Medicine, Journal of Bioinformatics and Computational Biology and Journal of the American Statistical Association.

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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