Alexis Nasr

157 total papers · 1.4k total citations
56 papers, 733 citations indexed

About

Alexis Nasr is a scholar working on Artificial Intelligence, Endocrinology, Diabetes and Metabolism and Computer Vision and Pattern Recognition. According to data from OpenAlex, Alexis Nasr has authored 56 papers receiving a total of 733 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 13 papers in Endocrinology, Diabetes and Metabolism and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Alexis Nasr's work include Natural Language Processing Techniques (28 papers), Topic Modeling (19 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (8 papers). Alexis Nasr is often cited by papers focused on Natural Language Processing Techniques (28 papers), Topic Modeling (19 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (8 papers). Alexis Nasr collaborates with scholars based in France, United States and Egypt. Alexis Nasr's co-authors include Owen Rambow, M. Breckwoldt, Joon Young Kim, Hala Tfayli, Silva Arslanian, Fida Bacha, SoJung Lee, Sara F. Michaliszyn, Frédéric Béchet and Sylvain Kahane and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, Diabetes Care and Diabetes.

In The Last Decade

Alexis Nasr

51 papers receiving 663 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Alexis Nasr 243 217 86 82 80 56 733
Akira Endoh 45 0.2× 211 1.0× 238 2.8× 80 1.0× 80 1.0× 37 710
Teresa M. A. Basile 274 1.1× 70 0.3× 83 1.0× 39 0.5× 43 0.5× 54 871
Katrine Meyer Lauritsen 222 0.9× 122 0.6× 103 1.2× 22 0.3× 103 1.3× 28 651
Jiancheng Dong 91 0.4× 70 0.3× 128 1.5× 39 0.5× 26 0.3× 58 774
Yan Yang 50 0.2× 235 1.1× 166 1.9× 37 0.5× 91 1.1× 33 694
Immacolata Cristina Nettore 27 0.1× 188 0.9× 173 2.0× 102 1.2× 37 0.5× 32 708
Weixiong Lin 105 0.4× 163 0.8× 197 2.3× 33 0.4× 174 2.2× 55 741
Ehab I. Mohamed 43 0.2× 62 0.3× 107 1.2× 75 0.9× 55 0.7× 60 891
Mitsuhiro Kometani 47 0.2× 354 1.6× 114 1.3× 45 0.5× 233 2.9× 71 659
Ting Lei 27 0.1× 83 0.4× 182 2.1× 48 0.6× 151 1.9× 52 909

Countries citing papers authored by Alexis Nasr

Since Specialization
Citations

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

Fields of papers citing papers by Alexis Nasr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexis Nasr

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

All Works

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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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