Sandra Bringay

1.5k total citations
62 papers, 725 citations indexed

About

Sandra Bringay is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Sandra Bringay has authored 62 papers receiving a total of 725 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Artificial Intelligence, 14 papers in Information Systems and 13 papers in Molecular Biology. Recurrent topics in Sandra Bringay's work include Data Mining Algorithms and Applications (13 papers), Topic Modeling (11 papers) and Biomedical Text Mining and Ontologies (9 papers). Sandra Bringay is often cited by papers focused on Data Mining Algorithms and Applications (13 papers), Topic Modeling (11 papers) and Biomedical Text Mining and Ontologies (9 papers). Sandra Bringay collaborates with scholars based in France, Spain and Chile. Sandra Bringay's co-authors include Jérôme Azé, Pascal Poncelet, Maguelonne Teisseire, Caroline Mollévi, Julien Rabatel, Paul Landais, Thomas Opitz, Maximilien Servajean, Jean Charlet and Arnaud Sallaberry and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and Journal of Medical Internet Research.

In The Last Decade

Sandra Bringay

58 papers receiving 693 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sandra Bringay France 15 270 173 97 85 82 62 725
Sai-fu Fung Hong Kong 15 313 1.2× 291 1.7× 74 0.8× 124 1.5× 152 1.9× 36 955
Michael B. Spring United States 16 305 1.1× 119 0.7× 228 2.4× 134 1.6× 279 3.4× 66 1.2k
Ramakanth Kavuluru United States 21 803 3.0× 187 1.1× 102 1.1× 83 1.0× 121 1.5× 72 1.4k
Sujin Kim United States 13 99 0.4× 105 0.6× 64 0.7× 100 1.2× 34 0.4× 50 789
Hui Yang China 18 94 0.3× 54 0.3× 186 1.9× 113 1.3× 27 0.3× 99 1.2k
V. G. Vinod Vydiswaran United States 18 398 1.5× 51 0.3× 97 1.0× 206 2.4× 23 0.3× 71 962
Jing Mei China 10 200 0.7× 103 0.6× 57 0.6× 29 0.3× 54 0.7× 58 434
Manas Gaur United States 17 390 1.4× 246 1.4× 94 1.0× 65 0.8× 139 1.7× 54 721
Brent Harrison United States 15 524 1.9× 75 0.4× 46 0.5× 177 2.1× 23 0.3× 44 915
Ashir Ahmed Japan 13 235 0.9× 181 1.0× 74 0.8× 88 1.0× 108 1.3× 119 938

Countries citing papers authored by Sandra Bringay

Since Specialization
Citations

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

Fields of papers citing papers by Sandra Bringay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sandra Bringay

This figure shows the co-authorship network connecting the top 25 collaborators of Sandra Bringay. A scholar is included among the top collaborators of Sandra Bringay 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 Sandra Bringay. Sandra Bringay 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.
Bonnet, Delphine, Sandra Bringay, Arnaud Sallaberry, et al.. (2025). Beyond single drivers: A multi-stressor framework for understanding and managing jellyfish proliferation under concurrent anthropogenic and climate pressures. Ocean & Coastal Management. 270. 107927–107927. 1 indexed citations
2.
Khier, Sonia, David Fabre, Jérôme Azé, et al.. (2025). Covariate Model Selection Approaches for Population Pharmacokinetics: A Systematic Review of Existing Methods, From SCM to AI. CPT Pharmacometrics & Systems Pharmacology. 14(4). 621–639. 1 indexed citations
3.
Azé, Jérôme, et al.. (2023). Explaining controversy through community analysis on Twitter. HAL (Le Centre pour la Communication Scientifique Directe). 148–155.
4.
Azé, Jérôme, et al.. (2022). EBBE-Text: Explaining Neural Networks by Exploring Text Classification Decision Boundaries. IEEE Transactions on Visualization and Computer Graphics. 29(10). 4154–4171. 8 indexed citations
5.
Azé, Jérôme, et al.. (2021). Sequential Pattern Mining to Predict Medical In-Hospital Mortality from Administrative Data: Application to Acute Coronary Syndrome. Journal of Healthcare Engineering. 2021. 1–12. 10 indexed citations
6.
Azé, Jérôme, et al.. (2019). Unveiling Online Suicide Behavior: What Can We Learn About Mental Health from Suicide Survivors of Reddit?. Studies in health technology and informatics. 264. 50–54. 12 indexed citations
7.
Azé, Jérôme, et al.. (2019). Attentive Multi-stage Learning for Early Risk Detection of Signs of Anorexia and Self-harm on Social Media.. HAL (Le Centre pour la Communication Scientifique Directe). 5 indexed citations
8.
9.
Bringay, Sandra, et al.. (2019). Complementary and Alternative Medicine in Patients With Breast Cancer: Exploratory Study of Social Network Forum Data. JMIR Cancer. 5(2). e12536–e12536. 17 indexed citations
10.
Azé, Jérôme, et al.. (2017). Raising Awareness About Cervical Cancer Using Twitter: Content Analysis of the 2015 #SmearForSmear Campaign. Journal of Medical Internet Research. 19(10). e344–e344. 41 indexed citations
11.
Bringay, Sandra, et al.. (2017). What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer. JMIR Medical Informatics. 5(3). e23–e23. 62 indexed citations
12.
Azé, Jérôme, et al.. (2017). Patient healthcare trajectory. An essential monitoring tool: a systematic review. Health Information Science and Systems. 5(1). 1–1. 32 indexed citations
13.
Fouillet, Anne, et al.. (2015). Surveillance et détection des événements inhabituels en toxicovigilance : revue des méthodes pertinentes. Revue d Épidémiologie et de Santé Publique. 63(2). 119–131. 2 indexed citations
14.
Bringay, Sandra, et al.. (2015). Mining closed partially ordered patterns, a new optimized algorithm. Knowledge-Based Systems. 79. 68–79. 10 indexed citations
15.
Bringay, Sandra, et al.. (2011). Mining microarray data to predict the histological grade of a breast cancer. Journal of Biomedical Informatics. 44. S12–S16. 10 indexed citations
16.
Bringay, Sandra, et al.. (2008). S 2 MP: similarity measure for sequential patterns. HAL (Le Centre pour la Communication Scientifique Directe). 87. 95–104. 14 indexed citations
17.
Bringay, Sandra, et al.. (2007). How to Represent the Medical Annotations. 2607. 2 indexed citations
18.
Bringay, Sandra, et al.. (2007). Informal notes to support the asynchronous collaborative activities. International Journal of Medical Informatics. 76. S342–S348. 7 indexed citations
19.
Bringay, Sandra, et al.. (2006). Annotations: A Functionality to support Cooperation, Coordination and Awareness in the Electronic Medical Record. 39–54. 10 indexed citations
20.
Bringay, Sandra, et al.. (2004). Les documents et les annotations du dossier patient hospitalier. HAL (Le Centre pour la Communication Scientifique Directe). 4 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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