opics: ? Federated learning frameworks and architectures for biomedical data. ? Privacy-preserving techniques in AI and their application to healthcare ? Case studies and real-world applications of federated learning in biomedical research.
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Conference Highlights
FPPAI@ICDCS25
Recent advances in Artificial Intelligence (AI) have revolutionized biomedical research, yet data privacy concerns often impede progress. This workshop addresses this critical challenge by focusing on federated learning and privacy-preserving AI techniques that enable collaborative research while ensuring data security and patient privacy. The workshop aims to bring together researchers, and industry experts to discuss the latest advancements and challenges in applying federated learning and privacy-preserving AI techniques to biomedical applications. The focus will be on ensuring data privacy and security while enabling collaborative research and innovation in healthcare.