Helena Geys

3.1k total citations
93 papers, 2.1k citations indexed

About

Helena Geys is a scholar working on Statistics and Probability, Management Science and Operations Research and Artificial Intelligence. According to data from OpenAlex, Helena Geys has authored 93 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Statistics and Probability, 22 papers in Management Science and Operations Research and 12 papers in Artificial Intelligence. Recurrent topics in Helena Geys's work include Statistical Methods in Clinical Trials (36 papers), Statistical Methods and Bayesian Inference (36 papers) and Optimal Experimental Design Methods (21 papers). Helena Geys is often cited by papers focused on Statistical Methods in Clinical Trials (36 papers), Statistical Methods and Bayesian Inference (36 papers) and Optimal Experimental Design Methods (21 papers). Helena Geys collaborates with scholars based in Belgium, United States and United Kingdom. Helena Geys's co-authors include Geert Molenberghs, Didier Renard, Marc Buyse, Tomasz Burzykowski, Tony Vangeneugden, Marc Aerts, Louise Ryan, Ariel Alonso, Annouschka Laenen and Christel Faes and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and International Journal of Cancer.

In The Last Decade

Helena Geys

88 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Helena Geys Belgium 25 944 406 240 210 187 93 2.1k
Didier Renard Belgium 21 633 0.7× 336 0.8× 177 0.7× 73 0.3× 98 0.5× 42 1.7k
Beat Neuenschwander Switzerland 22 1.5k 1.6× 545 1.3× 119 0.5× 227 1.1× 450 2.4× 44 2.4k
Kert Viele United States 21 474 0.5× 193 0.5× 247 1.0× 184 0.9× 89 0.5× 56 1.5k
Dipankar Bandyopadhyay United States 28 542 0.6× 174 0.4× 237 1.0× 344 1.6× 102 0.5× 182 2.6k
Heinz Schmidli Switzerland 31 1.1k 1.2× 368 0.9× 139 0.6× 274 1.3× 423 2.3× 78 2.6k
Thomas Jaki United Kingdom 29 1.5k 1.5× 579 1.4× 107 0.4× 243 1.2× 579 3.1× 173 2.8k
Alex Dmitrienko United States 27 1.3k 1.4× 488 1.2× 73 0.3× 304 1.4× 528 2.8× 75 2.3k
Haibo Zhou United States 36 856 0.9× 138 0.3× 100 0.4× 300 1.4× 91 0.5× 166 3.6k
Joachim Röhmel Germany 20 597 0.6× 158 0.4× 311 1.3× 292 1.4× 345 1.8× 58 1.5k
Joseph F. Heyse United States 24 451 0.5× 418 1.0× 62 0.3× 299 1.4× 176 0.9× 67 2.3k

Countries citing papers authored by Helena Geys

Since Specialization
Citations

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

Fields of papers citing papers by Helena Geys

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Helena Geys

This figure shows the co-authorship network connecting the top 25 collaborators of Helena Geys. A scholar is included among the top collaborators of Helena Geys 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 Helena Geys. Helena Geys 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.
Sargsyan, Davit, Javier Cabrera, Christine M. Livingston, et al.. (2023). Particle count estimation in dilution series experiments. Naval Research Logistics (NRL). 70(5). 472–479. 1 indexed citations
2.
Sargsyan, Davit, Javier Cabrera, Christine M. Livingston, et al.. (2023). Automated Spot Counting in Microbiology. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(6). 3703–3714. 1 indexed citations
3.
Rao, Mohan, Vahid Nassiri, Cristóbal Alhambra, et al.. (2023). AI/ML Models to Predict the Severity of Drug-Induced Liver Injury for Small Molecules. Chemical Research in Toxicology. 36(7). 1129–1139. 18 indexed citations
4.
Geys, Helena, et al.. (2020). Methods for Non-Compartmental Pharmacokinetic Analysis With Observations Below the Limit of Quantification. Statistics in Biopharmaceutical Research. 13(1). 59–70. 11 indexed citations
5.
Jacobs, Tom, Helena Geys, Thomas Jaki, et al.. (2019). Bayesian sequential integration within a preclinical pharmacokinetic and pharmacodynamic modeling framework: Lessons learned. Pharmaceutical Statistics. 18(4). 486–506. 4 indexed citations
6.
Elst, Wim Van der, Ariel Alonso, Helena Geys, et al.. (2019). Univariate Versus Multivariate Surrogates in the Single-Trial Setting. Statistics in Biopharmaceutical Research. 11(3). 301–310. 8 indexed citations
7.
Geys, Helena, et al.. (2018). Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies. Statistics in Biopharmaceutical Research. 10(4). 255–263. 3 indexed citations
8.
Jonghe, Sandra De, Petra Vinken, Bianca Feyen, et al.. (2014). Carcinogenicity in rats of the SGLT2 inhibitor canagliflozin. Chemico-Biological Interactions. 224. 1–12. 43 indexed citations
9.
Faes, Christel, Helena Geys, Marc Aerts, Paul J. Catalano, & Geert Molenberghs. (2012). Modelling Combined Continuous and Ordinal Outcomes from Developmental Toxicity Studies. Statistical Modelling. 247–254. 1 indexed citations
10.
Vangeneugden, Tony, Geert Molenberghs, Annouschka Laenen, et al.. (2010). Marginal Correlation in Longitudinal Binary Data Based on Generalized Linear Mixed Models. Communication in Statistics- Theory and Methods. 39(19). 3540–3557. 6 indexed citations
11.
Vangeneugden, Tony, Geert Molenberghs, Annouschka Laenen, et al.. (2010). Marginal correlation in longitudinal binary data based on generalized linear mixed models. Communications in Statistics - Simulation and Computation. 39(19). 3540–3557. 1 indexed citations
12.
Faes, Christel, Marc Aerts, Helena Geys, & Geert Molenberghs. (2007). Model Averaging Using Fractional Polynomials to Estimate a Safe Level of Exposure. Risk Analysis. 27(1). 111–123. 45 indexed citations
13.
Maringwa, John, et al.. (2007). On the Use of Historical Control Data in Pre-Clinical Safety Studies. Journal of Biopharmaceutical Statistics. 17(3). 493–509. 7 indexed citations
14.
Faes, Christel, Niel Hens, Marc Aerts, et al.. (2006). Estimating Herd-Specific Force of Infection by Using Random-Effects Models for Clustered Binary Data and Monotone Fractional Polynomials. Journal of the Royal Statistical Society Series C (Applied Statistics). 55(5). 595–613. 9 indexed citations
15.
Abrahantes, José Cortiñas, Jan Serroyen, Helena Geys, Geert Molenberghs, & Wilhelmus Drinkenburg. (2004). Statistical methods for EEG data. 65–130. 1 indexed citations
16.
Geys, Helena, Geert Molenberghs, & Paige L. Williams. (2002). Analysis of clustered binary data with covariates specific to each observation. Journal of Agricultural Biological and Environmental Statistics. 7. 1–15. 43 indexed citations
17.
Burzykowski, Tomasz, Geert Molenberghs, Marc Buyse, Helena Geys, & Didier Renard. (2001). Validation of Surrogate end Points in Multiple Randomized Clinical Trials with Failure Time end Points. Journal of the Royal Statistical Society Series C (Applied Statistics). 50(4). 405–422. 150 indexed citations
18.
Geys, Helena, et al.. (2001). Mapping cancer incidence in the province of Limburg, Belgium. Document Server@UHasselt (UHasselt). 1 indexed citations
19.
Buyse, Marc, Geert Molenberghs, Tomasz Burzykowski, Didier Renard, & Helena Geys. (2000). The validation of surrogate endpoints in meta-analyses of randomized experiments. Biostatistics. 1(1). 49–67. 428 indexed citations
20.
Geys, Helena, Geert Molenberghs, & Stuart R. Lipsitz. (1998). A note on the comparison of pseudo-likelihood and generalized estimating equations for marginally specified odds ratio models with exchangeable association structure. Journal of Statistical Computation and Simulation. 62(1-2). 45–71. 10 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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