Synthetic data are artificially generated datasets that retain the statistical properties of real healthcare data without compromising patient privacy. This guide explores how synthetic data empowers healthcare providers, researchers, government agencies, and life sciences organizations to accelerate research, improve patient outcomes, enable secure collaboration, and drive innovation. Unlike de-identified data, synthetic data ensure zero re-identification risk while maintaining utility. Created using methods like GANs and VAEs, synthetic data are validated to be statistically similar to real data, making them a powerful tool for AI/ML training, operational efficiency, and collaborative discovery.

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