Generative Artificial Intelligence: A Revolution in Patient Engagement and Personalized Treatment

Today, patient engagement has become a fundamental concept in improving the quality of healthcare services. The use of generative AI in this context can provide personalized solutions tailored to individual needs by analyzing patient data, thereby enhancing their quality of life. Moreover, generative AI can reduce the burden on healthcare systems by improving efficiency and facilitating decision-making processes, leading to more optimized resource management. This study aims to review the various applications of generative AI in enhancing patient interaction quality by exploring relevant methods and algorithms. Findings indicate that this technology can not only improve the prediction of treatment outcomes but also offer patients a unique experience and enhance the effectiveness of treatments. However, challenges such as data privacy and security remain critical barriers. This research also identifies areas that require further exploration and provides recommendations for future studies. The findings of this study can contribute to optimizing patient interaction models, improving therapeutic decision-making, and enhancing the quality of healthcare services through the utilization of generative AI.

Keywords:

generative AI , patient engagement , personalized treatment , large language models , data security