  The medical field is one of the important fields in the application of
artificial intelligence technology. With the explosive growth and
diversification of medical data, as well as the continuous improvement of
medical needs and challenges, artificial intelligence technology is playing an
increasingly important role in the medical field. Artificial intelligence
technologies represented by computer vision, natural language processing, and
machine learning have been widely penetrated into diverse scenarios such as
medical imaging, health management, medical information, and drug research and
development, and have become an important driving force for improving the level
and quality of medical services.The article explores the transformative
potential of generative AI in medical imaging, emphasizing its ability to
generate syntheticACM-2 data, enhance images, aid in anomaly detection, and
facilitate image-to-image translation. Despite challenges like model
complexity, the applications of generative models in healthcare, including
Med-PaLM 2 technology, show promising results. By addressing limitations in
dataset size and diversity, these models contribute to more accurate diagnoses
and improved patient outcomes. However, ethical considerations and
collaboration among stakeholders are essential for responsible implementation.
Through experiments leveraging GANs to augment brain tumor MRI datasets, the
study demonstrates how generative AI can enhance image quality and diversity,
ultimately advancing medical diagnostics and patient care.
