Generative Adversarial Networks (GANs) emerged as a breakthrough framework in deep learning and revolutionized synthetic data generation by pitting two neurons against each other in a competitive learning algorithm. GANs have proven to be a powerful tool for automated information processing in areas such as computer vision, natural language processing, healthcare, and design generation Moreover, in natural language processing in 2010, GANs have enabled text matching, speech synthesis, and language translation. The paper delves into the applications of GANs in healthcare, where they have contributed significantly to medical imaging, disease prognosis, and drug discovery by creating synthetic yet realistic medical data It happened, and protecting privacy and data confidentiality.