Marco Aldinucci

MERGE: A model for multi-input biomedical federated learning

2023 · Patterns

Driven by the deep learning (DL) revolution, artificial intelligence (AI) has become a fundamental tool for many biomedical tasks, including analyzing and classifying diagnostic images. Imaging, however, is not the only source of information. Tabular …

FedER: Federated Learning through Experience Replay and privacy-preserving data synthesis

2023 · Computer Vision and Image Understanding

In the medical field, multi-center collaborations are often sought to yield more generalizable findings by leveraging the heterogeneity of patient and clinical data. However, recent privacy regulations hinder the possibility to share data, and consequently, …

A Performance Analysis for Confidential Federated Learning

2024

Federated Learning (FL) has emerged as a solution to preserve data privacy by keeping the data locally on each participant’s device. However, FL alone is still vulnerable to attacks that can cause privacy leaks. Therefore, …