27 citations · 37 across the 6 of their papers we have counts for
9 papers
Post-clustering difference testing: valid inference and practical considerations
Benjamin Hivert, Denis Agniel, Rodolphe Thiébaut +1
Clustering is part of unsupervised analysis methods that consist in grouping samples into homogeneous and separate subgroups of observations also called clusters. To interpret the…
How to improve the quality of comparisons using external control cohorts in single-arm clinical trials?
Jérôme Lambert, Etienne Lengline, Raphaël Porcher +3
PURPOSE Providing rapid answers and early acces to patients to innovative treatments without randomized clinical trial (RCT) is growing, with benefit estimated from single-arm tria…
Evaluating the Use of Generalized Dynamic Weighted Ordinary Least Squares for Individualized HIV Treatment Strategies
Larry Dong, Erica E. M. Moodie, Laura Villain +1
Dynamic treatment regimes (DTR) are a statistical paradigm in precision medicine which aim to optimize patient outcomes by individualizing treatments. At its simplest, a DTR may re…
Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control approach
Quentin Clairon, Chloé Pasin, Irene Balelli +2
We present a parameter estimation method for nonlinear mixed effect models based on ordinary differential equations (NLME-ODEs). The method presented here aims at regularizing the…
EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models
Cédric Colas, Boris Hejblum, Sébastien Rouillon +4
Epidemiologists model the dynamics of epidemics in order to propose control strategies based on pharmaceutical and non-pharmaceutical interventions (contact limitation, lock down,…
Fréchet random forests for metric space valued regression with non euclidean predictors
Louis Capitaine, Jérémie Bigot, Rodolphe Thiébaut +1
Random forests are a statistical learning method widely used in many areas of scientific research because of its ability to learn complex relationships between input and output var…
Random forests for high-dimensional longitudinal data
Louis Capitaine, Robin Genuer, Rodolphe Thiébaut
Random forests is a state-of-the-art supervised machine learning method which behaves well in high-dimensional settings although some limitations may happen when , the number of…
Sequential Dirichlet Process Mixtures of Multivariate Skew t-distributions for Model-based Clustering of Flow Cytometry Data
Boris P. Hejblum, Chariff Alkhassim, Raphael Gottardo +2
Flow cytometry is a high-throughput technology used to quantify multiple surface and intracellular markers at the level of a single cell. This enables to identify cell sub-types, a…
Modeling CD4+ T cells dynamics in HIV-infected patients receiving repeated cycles of exogenous Interleukin 7
Ana Jarne, Daniel Commenges, Mélanie Prague +2
Combination Antiretroviral Therapy (cART) succeeds to control viral replication in most HIV infected patients. This is normally followed by a reconstitution of the CD4 T cells…