Abstract
<jats:p>The integration of Generative Artificial Intelligence (GenAI) is redefining healthcare by enhancing diagnosis, treatment, and research. This article explores how GenAI supports early disease detection, predictive modeling, and personalized care. Through real-world examples in fields like dermatology and radiology, it demonstrates GenAI's role in improving diagnostic accuracy and operational efficiency. Leveraging machine learning, deep learning, and natural language processing (NLP), the article highlights applications such as image classification, clinical text analysis, and interpretation of lab results. The use of synthetic data for research and training is also examined as a key innovation driver. In addition, the article addresses ethical and regulatory challenges, including data privacy and explainability, offering a practical framework for responsible GenAI adoption in clinical settings. It equips educators, researchers, and practitioners with insights to build scalable, inclusive, and intelligent healthcare systems.</jats:p>