New ways to use imaging data in cardiovascular research: survey of opinions on federated learning and synthetic data.

• Tác giả: Ross Forsyth, Jacqueline A L MacArthur, Steffen E Petersen, Michelle C Williams
• Ngôn ngữ: eng
• Ký hiệu phân loại: 629.229 *Other types of vehicles
• Thông tin xuất bản: England : European heart journal. Imaging methods and practice , 2025
• Bộ sưu tập: NCBI
• ID: 687418

Tóm tắt

AIMS: Federated learning and the creation of synthetic data are emerging tools, which may enhance the use of imaging data in cardiovascular research. This study sought to understand the perspectives of cardiovascular imaging researchers on the potential benefits and challenges associated with these technologies. METHODS AND RESULTS: The British Heart Foundation Data Science Centre conducted a series of online surveys and a virtual workshop to gather insights from stakeholders involved in cardiovascular imaging research about federated learning and synthetic data generation. The federated learning survey included 67 respondents: 18% ( CONCLUSION: Federated learning and synthetic data offer opportunities for advancing cardiovascular imaging research by addressing data privacy concerns and expanding data availability. However, challenges must be addressed to realize their full potential.