34 citations
- Université Paris CitéFR4 papers
- Assistance Publique – Hôpitaux de ParisFR3 papers
- Centre de Recherche sur l'InflammationFR3 papers
- InsermFR3 papers
- Sorbonne Paris CitéFR3 papers
- Université Paris-SaclayFR2 papers
- Bicêtre HospitalFR1 paper
- Bouygues (France)FR1 paper
- CEA Paris-SaclayFR1 paper
- CentraleSupélecFR1 paper
- Centre Cardiologique du NordFR1 paper
- Centre de Mathématiques Appliquées de l'École polytechniqueFR1 paper
5 papers
ONCOPILOT: A Promptable CT Foundation Model For Solid Tumor Evaluation
Léo Machado, Hélène Philippe, Élodie Ferreres +12
Carcinogenesis is a proteiform phenomenon, with tumors emerging in various locations and displaying complex, diverse shapes. At the crucial intersection of research and clinical pr…
Primary liver cancer classification from routine tumour biopsy using weakly supervised deep learning
Aurélie Beaufrère, Nora Ouzir, Paul Emile Zafar +8
The diagnosis of primary liver cancers (PLCs) can be challenging, especially on biopsies and for combined hepatocellular-cholangiocarcinoma (cHCC-CCA). We automatically classified…
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…
Multi-frequency MRE for elasticity quantitation and optimal tissue discrimination: a two-platform liver fibrosis mimicking phantom study
Fatiha Andoh, Jin Long Yue, Felicia Julea +8
In the framework of algebraic inversion, Magnetic Resonance Elastography (MRE) repeatability, reproducibility and robustness were evaluated on extracted shear velocities (or elasti…
Logistic Regression with Missing Covariates -- Parameter Estimation, Model Selection and Prediction within a Joint-Modeling Framework
Wei Jiang, Julie Josse, Marc Lavielle +1
Logistic regression is a common classification method in supervised learning. Surprisingly, there are very few solutions for performing logistic regression with missing values in t…