1 citations · 2 across the 6 of their papers we have counts for
6 papers
Adversarial Domain Adaptation Enables Knowledge Transfer Across Heterogeneous RNA-Seq Datasets
Kevin Dradjat, Massinissa Hamidi, Blaise Hanczar
Accurate phenotype prediction from RNA sequencing (RNA-seq) data is essential for diagnosis, biomarker discovery, and personalized medicine. Deep learning models have demonstrated…
Deep Generative Models for Discrete Genotype Simulation
Sihan Xie, Thierry Tribout, Didier Boichard +3
Deep generative models open new avenues for simulating realistic genomic data while preserving privacy and addressing data accessibility constraints. While previous studies have pr…
Self-supervised learning on gene expression data
Kevin Dradjat, Massinissa Hamidi, Pierre Bartet +1
Predicting phenotypes from gene expression data is a crucial task in biomedical research, enabling insights into disease mechanisms, drug responses, and personalized medicine. Trad…
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…
ECGrecover: a Deep Learning Approach for Electrocardiogram Signal Completion
Alex Lence, Federica Granese, Ahmad Fall +4
In this work, we address the challenge of reconstructing the complete 12-lead ECG signal from its incomplete parts. We focus on two main scenarios: (i) reconstructing missing signa…
SurvCaus : Representation Balancing for Survival Causal Inference
Ayoub Abraich, Agathe Guilloux, Blaise Hanczar
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 T…