AI and federated learning
Lingala Thirupathi, Sandeep Ravikanti, Vineetha Kaashipaka, Krishna Priya Thammana · 2025
Artificial Intelligence (AI) and Federated Learning (FL) are transforming research and treatment strategies for neural disorders by addressing the challenges of data silos and stringent privacy regulations. Federated learning, a decentralized ML, allows organizations to collaboratively train AI models on distributed datasets while maintaining patient confidentiality. This chapter examines how integrating AI and FL enhances personalized treatments, improves diagnostic accuracy, and promotes cross-institutional collaboration. It covers FL architectures, algorithms, optimization techniques, and applications, along with a discussion of the technical and ethical challenges, regulatory considerations, case studies, and future directions, all focused on accelerating discovery and enhancing patient care.