Agathe Guilloux

1.3k total citations
28 papers, 633 citations indexed

About

Agathe Guilloux is a scholar working on Statistics and Probability, Artificial Intelligence and Pathology and Forensic Medicine. According to data from OpenAlex, Agathe Guilloux has authored 28 papers receiving a total of 633 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Statistics and Probability, 10 papers in Artificial Intelligence and 6 papers in Pathology and Forensic Medicine. Recurrent topics in Agathe Guilloux's work include Statistical Methods and Inference (15 papers), Statistical Methods and Bayesian Inference (6 papers) and Genetic factors in colorectal cancer (6 papers). Agathe Guilloux is often cited by papers focused on Statistical Methods and Inference (15 papers), Statistical Methods and Bayesian Inference (6 papers) and Genetic factors in colorectal cancer (6 papers). Agathe Guilloux collaborates with scholars based in France, United States and United Kingdom. Agathe Guilloux's co-authors include Freddie Bray, Risto Sankila, Donald Maxwell Parkin, Alex Duval, Jean–François Fléjou, Stéphane Gaïffas, Olivier Buhard, Max Parkin, Hideaki Tsukuma and Wakiko Ajiki and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Agathe Guilloux

27 papers receiving 610 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Agathe Guilloux France 9 309 237 138 121 92 28 633
Alexandre A. Jácome Brazil 16 315 1.0× 94 0.4× 178 1.3× 153 1.3× 56 0.6× 45 574
H. Rauschecker Germany 15 345 1.1× 115 0.5× 98 0.7× 109 0.9× 164 1.8× 43 742
Leen Slaets Belgium 16 436 1.4× 282 1.2× 115 0.8× 130 1.1× 544 5.9× 45 960
Tuan Dinh United States 11 239 0.8× 164 0.7× 105 0.8× 178 1.5× 89 1.0× 24 578
Melissa Zhao United States 8 257 0.8× 108 0.5× 198 1.4× 96 0.8× 372 4.0× 15 909
Elizabeth M. Azzato United States 16 396 1.3× 142 0.6× 237 1.7× 58 0.5× 360 3.9× 43 956
G. Bastert Germany 17 494 1.6× 185 0.8× 80 0.6× 130 1.1× 339 3.7× 94 1.2k
B.M.P. Aleman Netherlands 7 182 0.6× 381 1.6× 229 1.7× 180 1.5× 85 0.9× 17 730
Kathryn Richert-Boe United States 17 531 1.7× 132 0.6× 393 2.8× 140 1.2× 137 1.5× 36 972
PA Fasching Germany 17 440 1.4× 108 0.5× 225 1.6× 93 0.8× 328 3.6× 92 969

Countries citing papers authored by Agathe Guilloux

Since Specialization
Citations

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

Fields of papers citing papers by Agathe Guilloux

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Agathe Guilloux

This figure shows the co-authorship network connecting the top 25 collaborators of Agathe Guilloux. A scholar is included among the top collaborators of Agathe Guilloux 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 Agathe Guilloux. Agathe Guilloux 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.
Laas, Enora, et al.. (2025). Evaluating breast cancer screening performance without registries using medico-administrative data. Scientific Reports. 15(1). 25096–25096.
2.
3.
Borget, Isabelle, et al.. (2023). Assessment of Performance, Interpretability, and Explainability in Artificial Intelligence–Based Health Technologies: What Healthcare Stakeholders Need to Know. SHILAP Revista de lepidopterología. 1(2). 120–138. 35 indexed citations
4.
Pécuchet, Nicolas, et al.. (2023). MS-CPFI: A model-agnostic Counterfactual Perturbation Feature Importance algorithm for interpreting black-box Multi-State models. Artificial Intelligence in Medicine. 147. 102741–102741. 3 indexed citations
5.
Bacry, Emmanuel, et al.. (2019). ConvSCCS: convolutional self-controlled case-seris model for lagged adverser event detection. HAL (Le Centre pour la Communication Scientifique Directe). 7 indexed citations
6.
Veil, Raphaël, Anita Burgun, Stéphane Gaïffas, et al.. (2019). Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework. BMC Medical Research Methodology. 19(1). 50–50. 10 indexed citations
7.
Jonchère, Vincent, Laëtitia Marisa, Agathe Guilloux, et al.. (2018). Identification of positively and negatively selected driver gene mutations associated with colorectal cancer with microsatellite instability. Annals of Oncology. 29. viii178–viii178. 1 indexed citations
8.
Guilloux, Agathe, et al.. (2016). Adaptive kernel estimation of the baseline function in the Cox model with high-dimensional covariates. Journal of Multivariate Analysis. 148. 141–159. 3 indexed citations
9.
Guilloux, Agathe, et al.. (2015). Adaptive estimation of the baseline hazard function in the Cox model by\n model selection, with high-dimensional covariates. arXiv (Cornell University). 3 indexed citations
10.
Guilloux, Agathe, et al.. (2014). A penalized algorithm for event-specific rate models for recurrent events. Biostatistics. 16(2). 281–294. 2 indexed citations
11.
Guilloux, Agathe, et al.. (2013). Estimation in a competing risks proportional hazards model under length-biased sampling with censoring. Lifetime Data Analysis. 20(2). 276–302. 2 indexed citations
12.
Guilloux, Agathe, et al.. (2011). Maximum likelihood estimator for cumulative incidence functions under proportionality constraint. Sankhya A. 73(2). 303–328. 2 indexed citations
13.
Guilloux, Agathe, et al.. (2009). Nonparametric density estimation in presence of bias and censoring. HAL (Le Centre pour la Communication Scientifique Directe). 15 indexed citations
14.
Zaanan, Aziz, Peggy Cuillière-Dartigues, Agathe Guilloux, et al.. (2009). Impact of p53 expression and microsatellite instability on stage III colon cancer disease-free survival in patients treated by 5-fluorouracil and leucovorin with or without oxaliplatin. Annals of Oncology. 21(4). 772–780. 99 indexed citations
15.
Guilloux, Agathe, Peggy Dartigues, Étienne Loire, et al.. (2008). Nonsense-Mediated mRNA Decay Impacts MSI-Driven Carcinogenesis and Anti-Tumor Immunity in Colorectal Cancers. PLoS ONE. 3(7). e2583–e2583. 34 indexed citations
16.
Guilloux, Agathe, et al.. (2007). Nonparametric inference under competing risks and selection-biased sampling. Journal of Multivariate Analysis. 99(4). 589–605. 5 indexed citations
17.
Guilloux, Agathe. (2007). Nonparametric estimation for censored lifetimes suffering from unknown selection bias. Mathematical Methods of Statistics. 16(3). 202–216. 3 indexed citations
18.
Guilloux, Agathe, et al.. (2005). Nonparametric estimation from proportional hazards competing risks data under selection bias. Journal of nonparametric statistics. 17(6). 717–731. 1 indexed citations
19.
Bray, Freddie, Agathe Guilloux, Risto Sankila, & Donald Maxwell Parkin. (2002). Practical implications of imposing a new world standard population. Cancer Causes & Control. 13(2). 175–182. 91 indexed citations
20.
Lambert, René, Agathe Guilloux, Akira Oshima, et al.. (2001). Incidence and mortality from stomach cancer in Japan, Slovenia and the USA. International Journal of Cancer. 97(6). 811–818. 109 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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