Abstract

Artificial Intelligence (AI) has emerged as a transformative tool in the field of medical diagnostics, particularly in the identification and management of rare diseases. This article explores the current trends and future directions of AI applications in diagnosing rare diseases, highlighting advancements in machine learning algorithms, data integration techniques, and predictive modeling. We analyze recent case studies and research to assess the effectiveness of AI in improving diagnostic accuracy and speed, and discuss the challenges and limitations associated with its implementation. The paper concludes with recommendations for future research and development in this evolving field.