The Role of Generative Models in Modern Healthcare

Generative models, span from GANs, VAEs, and Diffusion Models, are revolutionizing the-healthcare domain using fake data, enhancing medical images, and enhancing drug purposes. GANs optimize image reconstruction by increasing the PSNR by approximately 23%, whereas diffusion models produced a test accuracy of over 95% in molecular simulations. VAEs are particularly suitable for predictive modelling for decision support in the field of pharmacogenomics to improve patient outcome prognosis by 15%. This chapter provides a discussion of the architectural development and deployment of these models in data-driven and privacy-preserving healthcare. Quantitative and qualitative comparisons with other methods are given, e.g., GANs are stated to decrease drug discovery time by 70%; problems and limitations, including mode collapse and model interpretability, are mentioned. The future directions discussed here are the hybrid model designs and the possibility of the large-scale implementation of generative models as critical elements of present-day healthcare.

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