Federated Learning (FL) has gained significant attention as a novel distributed machine learning paradigm that enables collaborative model training while preserving data privacy. However, traditional ...

One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...

Open-Source Hybrid Large Language Model Integrated System for Extraction of Breast Cancer Treatment Pathway From Free-Text Clinical Notes Federated learning (FL) enables multi-institutional predictive ...

The Hong Kong Applied Science and Technology Research Institute (ASTRI) joins forces with tech-embracing companies to leverage a privacy-preserving technology, called “Federated Learning”, to develop ...