Federated learning as a catalyst for digital healthcare innovations
Guang Yang, Brandon Edwards, Spyridon Bakas, Qi Dou, Daguang Xu, Xiaoxiao Li, Wanying Wang · Patterns · 2024
As the landscape of digital healthcare continues to evolve, the integration of artificial intelligence (AI) presents both immense opportunities and profound challenges. At the heart of this dynamic field lies the quest for innovative solutions that enhance patient care while safeguarding sensitive medical data. In response to these imperatives, the emergence of federated learning (FL) represents a pivotal advancement, offering a pathway to harness the collective intelligence of distributed healthcare datasets while respecting privacy and security protocols.