Generative AI in Healthcare: Balancing Opportunities & Risks from Research to Diagnostics
Over the past decade, AI has been gradually transforming healthcare by facilitating data-driven decision-making and improving clinical outcomes. In recent years, a new branch of AI, generative AI, in healthcare has gained significant attention due to its ability to generate new content, including medical summaries, imaging simulations, treatment recommendations, and predictive models.
In contrast to standard AI systems that primarily analyse and classify existing data, Generative AI models learn patterns from large datasets and generate new outputs based on those patterns. Furthermore, to accelerate research, automate administrative tasks, and improve clinical support systems, large language models, generative adversarial networks (GANs), and diffusion models are increasingly employed in healthcare.
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