output
20212026
most citedThe Smart Data Extractor, a Clinician Friendly Solution to Accelerate and Improve the Data Collection During Clinical Trials

5 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

4 papers

cs.AI2026

AAbAAC: An Annotated Corpus for Autoimmunity Information Extraction

Fabien Maury, Solène Grosdidier, Maud de Dieuleveult +1

Despite advances in information extraction driven by deep learning and large language models, performance gaps remain in highly specialized biomedical fields, where domainspecific…

eess.IV2026

SCALMU: Synthetically-trained Coupling of Adaptive Learned Multiplicative Updates for Hyperspectral-Multispectral Fusion

Xinxin Xu, Yann Gousseau, Christophe Kervazo +1

HyperSpectral-MultiSpectral Image (HSI-MSI) fusion aims to recover a high-resolution hyperspectral image from a low-resolution HSI and a high-resolution MSI. Classical methods such…

q-bio.QM2023★ 5 cited

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…

cs.CV2021

Automatic size and pose homogenization with spatial transformer network to improve and accelerate pediatric segmentation

Giammarco La Barbera, Pietro Gori, Haithem Boussaid +6

Due to a high heterogeneity in pose and size and to a limited number of available data, segmentation of pediatric images is challenging for deep learning methods. In this work, we…