the introduction:<br />Recent developments in the field of medical technology and artificial intelligence techniques represent an important shift in improving the diagnosis and treatment of eye diseases. Retinal degeneration is one of the common and serious eye diseases that can be diagnosed more accurately using artificial intelligence applications. This article aims to explore how smart technologies can be used in diagnosing retinal degeneration and analyze their importance in improving patient care.<br />Part One: The concept of retinal degeneration<br />This part discusses the concept of retinal degeneration, the factors that contribute to its development, and its impact on vision. It also discusses the traditional techniques used in its diagnosis.<br />Part Two: Foundations of artificial intelligence in diagnosing retinal degeneration<br />This part provides an overview of how smart technologies can be integrated into the diagnosis of retinal degeneration, focusing on the basics of artificial intelligence and its applications in medicine.<br />Part Three: The roles of artificial intelligence applications in diagnosing retinal degeneration<br />This section reviews the potential roles that AI applications can play in diagnosing retinal degeneration, including image analysis, predicting disease progression, and providing personalized treatment options.<br />Part Four: Challenges and opportunities for using artificial intelligence applications in diagnosing retinal degeneration<br />This section discusses potential challenges in using AI applications, such as security and privacy, as well as opportunities to improve diagnosis and provide more accurate treatments.<br />Part Five: Results and recommendations<br />This section concludes by summarizing the results and providing recommendations for future research and applications of artificial intelligence in the diagnosis and treatment of retinal degeneration.<br />Conclusion:<br />This article highlights the importance of using artificial intelligence applications to improve the diagnosis of retinal degeneration, focusing on future challenges and opportunities.