In the rapidly evolving healthcare field, integrating advanced artificial intelligence (AI) technologies presents unprecedented opportunities for improving patient outcomes while safeguarding privacy. This talk, "Secure and Smart: Federated Learning in Healthcare's Future," explores how Federated Learning and Edge Computing revolutionize how we approach healthcare data. Federated Learning enables collaborative AI model training across decentralized data sources, allowing healthcare providers to leverage global insights without compromising sensitive patient information. By combining this with Edge Computing, we can achieve real-time data processing with enhanced privacy, setting the stage for a new era of secure and efficient healthcare solutions.
The presentation will also delve into the roles of Large and Small Language Models (LLMs and SLMs), examining their respective strengths in various healthcare applications. Real-world case studies, including groundbreaking work by Intel, Penn Medicine, and Rhino Health, will illustrate the practical impacts of these technologies. Additionally, we will discuss the challenges of adopting these innovations, from data privacy to computational limitations, and how overcoming these hurdles can lead to a more secure, collaborative future in healthcare. Join us as we explore the cutting-edge of AI in healthcare and its potential to transform the industry.
#federatedlearning #edgecomputing #llm
