Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?

Understand

After being collected for patient care, Observational Health Data (OHD) can further benefit patient well-being by sustaining the development of health informatics and medical research.

• Vast potential is unexploited because of the fiercely private nature of patient-related data and regulations to protect it.
• Generative Adversarial Networks (GANs) have recently emerged as a groundbreaking way to learn generative models that produce realistic synthetic data.
• They have revolutionized practices in multiple domains such as self-driving cars, fraud detection, digital twin simulations in industrial sectors, and medical imaging.