Generative AI in Healthcare: An Analytical Review of Models, Clinical Applications, and Decision-Support Implications
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Journal of Future Artificial Intelligence and Technologies (FAITH) - Future Techno Science
خلاصة
This review examines the rapidly expanding landscape of Generative Artificial Intelligence (GenAI) in healthcare, focusing on how models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), diffusion models, and large language models are being explored across various medical domains. It highlights their applications in medical imaging, clinical documentation, synthetic data generation, and decision-support systems. The study also discusses the benefits of these technologies in improving efficiency, accuracy, and personalization in healthcare. Furthermore, it addresses key challenges, including data privacy, ethical considerations, and model reliability. The review concludes by emphasizing the transformative potential of generative AI while underscoring the need for careful implementation and regulation.