Trilemma in Generating Realistic Yet Synthetic Healthcare Data: On Realism, Security, and Utility

<b>Author:</b> <br>Nicholas I-Hsien Kuo, <br>Centre for Big Data Research in Health (CBDRH), <br>University of New South Wales, Sydney, Australia<br><b>Description:</b><br>This presentation was prepared for the <br>2025 National Big Data Health Science Conference in Columbia, SC, USA. <br>It showcases research from the <br>Centre for Big Data Research in Health (CBDRH), UNSW, <br>focusing on leveraging synthetic data to enhance accessibility <br>for research and education. <br>The presentation covers the challenges of realism, security, and utility <br>in synthetic data generation and how our research addresses these issues.<br>🔗 For more research and datasets, visit:<br>Nicholas Kuo’s Figshare Profile