8 citations · 13 across the 15 of their papers we have counts for
19 papers
Cardiac Output Prediction from Echocardiograms: Self-Supervised Learning with Limited Data
Adson Duarte, Davide Vitturini, Emanuele Milillo +9
Cardiac Output (CO) is a key parameter in the diagnosis and management of cardiovascular diseases. However, its accurate measurement requires right-heart catheterization, an invasi…
Automated Prediction of Paravalvular Regurgitation before Transcatheter Aortic Valve Implantation
Michele Cannito, Riccardo Renzulli, Adson Duarte +9
Severe aortic stenosis is a common and life-threatening condition in elderly patients, often treated with Transcatheter Aortic Valve Implantation (TAVI). Despite procedural advance…
Stacked Regression using Off-the-shelf, Stimulus-tuned and Fine-tuned Neural Networks for Predicting fMRI Brain Responses to Movies (Algonauts 2025 Report)
Robert Scholz, Kunal Bagga, Christine Ahrends +1
We present our submission to the Algonauts 2025 Challenge, where the goal is to predict fMRI brain responses to movie stimuli. Our approach integrates multimodal representations fr…
Robust brain age estimation from structural MRI with contrastive learning
Carlo Alberto Barbano, Benoit Dufumier, Edouard Duchesnay +2
Estimating brain age from structural MRI has emerged as a powerful tool for characterizing normative and pathological aging. In this work, we explore contrastive learning as a scal…
If you can describe it, they can see it: Cross-Modal Learning of Visual Concepts from Textual Descriptions
Carlo Alberto Barbano, Luca Molinaro, Massimiliano Ciranni +3
Humans can visualize new and unknown concepts from their natural language description, based on their experience and previous knowledge. Insipired by this, we present a way to exte…
Say My Name: a Model's Bias Discovery Framework
Massimiliano Ciranni, Luca Molinaro, Carlo Alberto Barbano +4
In the last few years, due to the broad applicability of deep learning to downstream tasks and end-to-end training capabilities, increasingly more concerns about potential biases t…