103 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- InsermFR26 papers
- Sorbonne UniversitéFR23 papers
- Université Paris CitéFR20 papers
- Assistance Publique – Hôpitaux de ParisFR11 papers
- Centre National de la Recherche ScientifiqueFR10 papers
- Heka : Méthodes basées sur les données et modèles en santé pour l'acquisition de connaissancesFR9 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR8 papers
- École PolytechniqueFR8 papers
- Institut national de recherche en sciences et technologies du numériqueFR8 papers
- Sorbonne Paris CitéFR7 papers
- Institut du CerveauFR6 papers
- Hôpital Européen Georges-PompidouFR4 papers
32 papers
QUARTZ : QA-based Unsupervised Abstractive Refinement for Task-oriented Dialogue Summarization
Mohamed Imed Eddine Ghebriout, Gaël Guibon, Ivan Lerner +1
Dialogue summarization aims to distill the core meaning of a conversation into a concise text. This is crucial for reducing the complexity and noise inherent in dialogue-heavy appl…
Wavelet-Based Multiscale Flow For Realistic Image Deformation in the Large Diffeomorphic Deformation Model Framework
Fleur Gaudfernau, Eléonore Blondiaux, Stéphanie Allassonnière +1
Estimating accurate high-dimensional transformations remains very challenging, especially in a clinical setting. In this paper, we introduce a multiscale parameterization of deform…
Straightforward Phase I Dose-Finding Design for Healthy Volunteers Accounting for Surrogate Activity Biomarkers
Sandrine Boulet, Emmanuelle Comets, Antoine Guillon +5
Conventionally, a first-in-human phase I trial in healthy volunteers aims to confirm the safety of a drug in humans. In such situations, volunteers should not suffer from any safet…
ABiMed: An intelligent and visual clinical decision support system for medication reviews and polypharmacy management
Abdelmalek Mouazer, Romain Léguillon, Nada Boudegzdame +14
Background: Polypharmacy, i.e. taking five drugs or more, is both a public health and an economic issue. Medication reviews are structured interviews of the patient by the communit…
FedECA: Federated External Control Arms for Causal Inference with Time-To-Event Data in Distributed Settings
Jean Ogier du Terrail, Quentin Klopfenstein, Honghao Li +22
External control arms can inform early clinical development of experimental drugs and provide efficacy evidence for regulatory approval. However, accessing sufficient real-world or…
T-Rep: Representation Learning for Time Series using Time-Embeddings
Archibald Fraikin, Adrien Bennetot, Stéphanie Allassonnière
Multivariate time series present challenges to standard machine learning techniques, as they are often unlabeled, high dimensional, noisy, and contain missing data. To address this…
The Smart Data Extractor, a Clinician Friendly Solution to Accelerate and Improve the Data Collection During Clinical Trials
Sophie Quennelle, Maxime Douillet, Lisa Friedlander +4
In medical research, the traditional way to collect data, i.e. browsing patient files, has been proven to induce bias, errors, human labor and costs. We propose a semi-automated sy…
Variational Inference for Longitudinal Data Using Normalizing Flows
Clément Chadebec, Stéphanie Allassonnière
This paper introduces a new latent variable generative model able to handle high dimensional longitudinal data and relying on variational inference. The time dependency between the…
Learning the Dynamics of Sparsely Observed Interacting Systems
Linus Bleistein, Adeline Fermanian, Anne-Sophie Jannot +1
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…
Bayesian Framework for Multi-Source Data Integration -- Application to Human Extrapolation From Preclinical Studies
Sandrine Boulet, Moreno Ursino, Robin Michelet +4
In preclinical investigations, e.g. in in vitro, in vivo and in silico studies, the pharmacokinetic, pharmacodynamic and toxicological characteristics of a drug are evaluated befor…
A straightforward meta-analysis approach for oncology phase I dose-finding studies
Christian Röver, Moreno Ursino, Tim Friede +1
Phase I early-phase clinical studies aim at investigating the safety and the underlying dose-toxicity relationship of a drug or combination. While little may still be known about t…
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder
Clément Chadebec, Elina Thibeau-Sutre, Ninon Burgos +1
In this paper, we propose a new method to perform data augmentation in a reliable way in the High Dimensional Low Sample Size (HDLSS) setting using a geometry-based variational aut…
Data Augmentation with Variational Autoencoders and Manifold Sampling
Clément Chadebec, Stéphanie Allassonnière
We propose a new efficient way to sample from a Variational Autoencoder in the challenging low sample size setting. This method reveals particularly well suited to perform data aug…
Bayesian dose-regimen assessment in early phase oncology incorporating pharmacokinetics and pharmacodynamics
Emma Gerard, Sarah Zohar, Hoai-Thu Thai +3
Phase I dose-finding trials in oncology seek to find the maximum tolerated dose (MTD) of a drug under a specific schedule. Evaluating drug-schedules aims at improving treatment saf…
Discovering alignment relations with Graph Convolutional Networks: a biomedical case study
Pierre Monnin, Chedy Raïssi, Amedeo Napoli +1
Knowledge graphs are freely aggregated, published, and edited in the Web of data, and thus may overlap. Hence, a key task resides in aligning (or matching) their content. This task…
Optimisation des parcours patients pour lutter contre l'errance de diagnostic des patients atteints de maladies rares
Frédéric Logé, Rémi Besson, Stéphanie Allassonnière
A patient suffering from a rare disease in France has to wait an average of two years before being diagnosed. This medical wandering is highly detrimental both for the health syste…
Geometry-Aware Hamiltonian Variational Auto-Encoder
Clément Chadebec, Clément Mantoux, Stéphanie Allassonnière
Variational auto-encoders (VAEs) have proven to be a well suited tool for performing dimensionality reduction by extracting latent variables lying in a potentially much smaller dim…
Personalized Dynamic Treatment Regimes in Continuous Time: A Bayesian Approach for Optimizing Clinical Decisions with Timing
William Hua, Hongyuan Mei, Sarah Zohar +2
Accurate models of clinical actions and their impacts on disease progression are critical for estimating personalized optimal dynamic treatment regimes (DTRs) in medical/health res…
Gaussian Graphical Model exploration and selection in high dimension low sample size setting
Thomas Lartigue, Simona Bottani, Stephanie Baron +3
Gaussian Graphical Models (GGM) are often used to describe the conditional correlations between the components of a random vector. In this article, we compare two families of GGM i…
Deterministic Approximate EM Algorithm; Application to the Riemann Approximation EM and the Tempered EM
Thomas Lartigue, Stanley Durrleman, Stéphanie Allassonnière
The Expectation Maximisation (EM) algorithm is widely used to optimise non-convex likelihood functions with latent variables. Many authors modified its simple design to fit more sp…
Random-effects meta-analysis of phase I dose-finding studies using stochastic process priors
Moreno Ursino, Christian Röver, Sarah Zohar +1
Phase I dose-finding studies aim at identifying the maximal tolerated dose (MTD). It is not uncommon that several dose-finding studies are conducted, although often with some varia…
Mechanical characterization of cells and microspheres sorted by acoustophoresis with in-line resistive pulse sensing
Antoine Riaud, Anh L. P. Thai, Wei Wang +1
Resistive Pulse Sensing (RPS) is a key label-free technology to measure particles and single-cell size distribution. As a growing corpus of evidence supports that cancer cells exhi…
Transscleral Optical Phase Imaging of the Human Retina - TOPI
Timothé Laforest, Mathieu Künzi, Laura Kowalczuk +3
The in vivo observation of the human retina at the cellular level is crucial to detect lesions before irreversible visual loss occurs, to follow the time course of retinal diseases…
Simulation of virtual cohorts increases predictive accuracy of cognitive decline in MCI subjects
Igor Koval, Stéphanie Allassonnière, Stanley Durrleman
The ability to predict the progression of biomarkers, notably in NDD, is limited by the size of the longitudinal data sets, in terms of number of patients, number of visits per pat…