From the 1 of 5 linked papers with an AI index.
5 papers
Foundational values for foundation models
John S. H. Baxter, Elodie Germani
Research values, properties with a distinctive normative dimension, often affect how technological research is performed in both direct and indirect ways by influencing how technic…
Multi-scale radiomics in pelvic MRI for endometriosis subtyping: highlighting data heterogeneity constraints
Eliot Leguy, Chloe Mallet, Nicolas Normand +1
The paper evaluates a radiomics pipeline on pelvic MRI to subtype endometriosis, comparing multi‑scale feature representations and showing modest classification performance but lim…
Disentangling Prompt Dependence to Evaluate Segmentation Reliability in Gynecological MRI
Elodie Germani, Krystel Nyangoh-Timoh, Pierre Jannin +1
Promptable segmentation models (e.g., the Segment Anything Models) enable generalizable, zero-shot segmentation across diverse domains. Although predictions are deterministic for a…
MRIQT: Physics-Aware Diffusion Model for Image Quality Transfer in Neonatal Ultra-Low-Field MRI
Malek Al Abed, Sebiha Demir, Anne Groteklaes +4
Portable ultra-low-field MRI (uLF-MRI, 0.064 T) offers accessible neuroimaging for neonatal care but suffers from low signal-to-noise ratio and poor diagnostic quality compared to…
Bias and Generalizability of Foundation Models across Datasets in Breast Mammography
Elodie Germani, Ilayda Selin Türk, Fatima Zeineddine +2
Over the past decades, computer-aided diagnosis tools for breast cancer have been developed to enhance screening procedures, yet their clinical adoption remains challenged by data…