2.2k citations
- Sorbonne UniversitéFR66 papers
- Centre National de la Recherche ScientifiqueFR57 papers
- Institut du CerveauFR52 papers
- InsermFR51 papers
- Assistance Publique – Hôpitaux de ParisFR49 papers
- Institut des Sciences MoléculairesFR13 papers
- Institut national de recherche en sciences et technologies du numériqueFR10 papers
- Université Pierre-et-Marie-CurieFR10 papers
- Université de LilleFR9 papers
- ARAMIS: Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain sain et pathologiqueFR8 papers
- Translational Innovation in Medicine and ComplexityFR7 papers
- Université Paris CitéFR7 papers
86 papers
Prior-Data Fitted Networks for Causal Inference: a Simulation Study with Real-World Scenarios
Francisco Mourao, David Hajage, Daria Bystrova +4
Prior-Data Fitted Networks (PFNs) represent a paradigm shift in tabular data prediction. We present the principles of this new paradigm and evaluate two PFNs for estimating the ave…
Performance uncertainty in medical image analysis: a large-scale investigation of confidence intervals
Pascaline André, Charles Heitz, Evangelia Christodoulou +10
Performance uncertainty quantification is essential for reliable validation and eventual clinical translation of medical imaging artificial intelligence (AI). Confidence intervals…
Multi-Domain Brain Vessel Segmentation Through Feature Disentanglement
Francesco Galati, Daniele Falcetta, Rosa Cortese +3
The intricate morphology of brain vessels poses significant challenges for automatic segmentation models, which usually focus on a single imaging modality. However, accurately trea…
Unsupervised anomaly detection using Bayesian flow networks: application to brain FDG PET in the context of Alzheimer's disease
Hugues Roy, Reuben Dorent, Ninon Burgos
Unsupervised anomaly detection (UAD) plays a crucial role in neuroimaging for identifying deviations from healthy subject data and thus facilitating the diagnosis of neurological d…
Development and Comparative Evaluation of Three Artificial Intelligence Models (NLP, LLM, JEPA) for Predicting Triage in Emergency Departments: A 7-Month Retrospective Proof-of-Concept
Edouard Lansiaux, Ramy Azzouz, Emmanuel Chazard +2
Emergency departments struggle with persistent triage errors, especially undertriage and overtriage, which are aggravated by growing patient volumes and staff shortages. This study…
Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy
Martin Guillemaud, Alice Longhena, Louis Cousyn +4
Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option for patients with drug-resistant seizures. However, accurately predicting surgical…