Zobrazeno 1 - 10
of 151
pro vyhledávání: '"Guilloux, Agathe"'
We consider the task of learning individual-specific intensities of counting processes from a set of static variables and irregularly sampled time series. We introduce a novel modelization approach in which the intensity is the solution to a controll
Externí odkaz:
http://arxiv.org/abs/2401.17077
Autor:
Nguyen, Van Tuan, Fermanian, Adeline, Guilloux, Agathe, Barbieri, Antoine, Zohar, Sarah, Jannot, Anne-Sophie, Bussy, Simon
This paper introduces a prognostic method called FLASH that addresses the problem of joint modelling of longitudinal data and censored durations when a large number of both longitudinal and time-independent features are available. In the literature,
Externí odkaz:
http://arxiv.org/abs/2309.03714
Autor:
Bleistein, Linus, Guilloux, Agathe
Neural Controlled Differential Equations (NCDEs) are a state-of-the-art tool for supervised learning with irregularly sampled time series (Kidger, 2020). However, no theoretical analysis of their performance has been provided yet, and it remains uncl
Externí odkaz:
http://arxiv.org/abs/2305.16791
We address the problem of learning the dynamics of an unknown non-parametric system linking a target and a feature time series. The feature time series is measured on a sparse and irregular grid, while we have access to only a few points of the targe
Externí odkaz:
http://arxiv.org/abs/2301.11647
With the increased availability of large health databases comes the opportunity of evaluating treatment effect on new data sources.Through these databases time-dependent outcomes can be analysed as events that can be measured using counting processes
Externí odkaz:
http://arxiv.org/abs/2204.03447
Individual Treatment Effects (ITE) estimation methods have risen in popularity in the last years. Most of the time, individual effects are better presented as Conditional Average Treatment Effects (CATE). Recently, representation balancing techniques
Externí odkaz:
http://arxiv.org/abs/2203.15672
Publikováno v:
In Artificial Intelligence In Medicine January 2024 147
Autor:
Farah, Line, Murris, Juliette M., Borget, Isabelle, Guilloux, Agathe, Martelli, Nicolas M., Katsahian, Sandrine I.M.
Publikováno v:
In Mayo Clinic Proceedings: Digital Health June 2023 1(2):120-138
Autor:
Sobrino, Steicy, Magnani, Alessandra, Semeraro, Michaela, Martignetti, Loredana, Cortal, Akira, Denis, Adeline, Couzin, Chloé, Picard, Capucine, Bustamante, Jacinta, Magrin, Elisa, Joseph, Laure, Roudaut, Cécile, Gabrion, Aurélie, Soheili, Tayebeh, Cordier, Corinne, Lortholary, Olivier, Lefrere, François, Rieux-Laucat, Frédéric, Casanova, Jean-Laurent, Bodard, Sylvain, Boddaert, Nathalie, Thrasher, Adrian J., Touzot, Fabien, Taque, Sophie, Suarez, Felipe, Marcais, Ambroise, Guilloux, Agathe, Lagresle-Peyrou, Chantal, Galy, Anne, Rausell, Antonio, Blanche, Stephane, Cavazzana, Marina, Six, Emmanuelle
Publikováno v:
In Cell Reports Medicine 21 February 2023 4(2)
Autor:
Bussy, Simon, Veil, Raphaël, Looten, Vincent, Burgun, Anita, Gaïffas, Stéphane, Guilloux, Agathe, Ranque, Brigitte, Jannot, Anne-Sophie
Background: Choosing the most performing method in terms of outcome prediction or variables selection is a recurring problem in prognosis studies, leading to many publications on methods comparison. But some aspects have received little attention. Fi
Externí odkaz:
http://arxiv.org/abs/1807.09821