activity
20242026
collaborators

6 papers

q-bio.GN2026

MetagenBERT: a Transformer-based Architecture using Foundational genomic Large Language Models for novel Metagenome Representation

Gaspar Roy, Eugeni Belda, Baptiste Hennecart +3

Metagenomic disease prediction commonly relies on species abundance tables derived from large, incomplete reference catalogs, constraining resolution and discarding valuable inform…

cs.CV2025

SIM-Net: A Multimodal Fusion Network Using Inferred 3D Object Shape Point Clouds from RGB Images for 2D Classification

Youcef Sklab, Hanane Ariouat, Eric Chenin +2

We introduce the Shape-Image Multimodal Network (SIM-Net), a novel 2D image classification architecture that integrates 3D point cloud representations inferred directly from RGB im…

cs.CV2025

IKrNet: A Neural Network for Detecting Specific Drug-Induced Patterns in Electrocardiograms Amidst Physiological Variability

Ahmad Fall, Federica Granese, Alex Lence +5

Monitoring and analyzing electrocardiogram (ECG) signals, even under varying physiological conditions, including those influenced by physical activity, drugs and stress, is crucial…

cs.CL2025

Prompting ChatGPT for Chinese Learning as L2: A CEFR and EBCL Level Study

Miao Lin-Zucker, Joël Bellassen, Jean-Daniel Zucker

The use of chatbots in language learning has evolved significantly since the 1960s, becoming more sophisticated platforms as generative AI emerged. These tools now simulate natural…

eess.SP2024

ECGtizer: a fully automated digitizing and signal recovery pipeline for electrocardiograms

Alex Lence, Ahmad Fall, Samuel David Cohen +4

Electrocardiograms (ECGs) are essential for diagnosing cardiac pathologies, yet traditional paper-based ECG storage poses significant challenges for automated analysis. This study…

cs.LG2024

A text-to-tabular approach to generate synthetic patient data using LLMs

Margaux Tornqvist, Jean-Daniel Zucker, Tristan Fauvel +3

Access to large-scale high-quality healthcare databases is key to accelerate medical research and make insightful discoveries about diseases. However, access to such data is often…