The Role of AI in Early Diagnosis, Management, and Clinical Research of Primary Immunodeficiency Diseases: Insights from GCC Immunologists

Abstract

Primary Immunodeficiency Diseases (PIDs) are a family of approximately 450 rare disorders each with distinct diagnostic challenges because of their diverse clinical signs and the community’s limited knowledge of them. Because of these challenges, patients receive their diagnoses later than optimal, tend to experience more complications, and generally receive suboptimal care. The correct and timely identification of patients with PIDs remains critical because it allows for a better prognosis as well as timely and effective management. The advancements in artificial intelligence, especially machine learning and natural language processing show potential to address current challenges in the early diagnosis of PIDs and the development of optimal management and research strategies. This study aims to investigate the perception of immunologists from GCC countries on the application of AI in the diagnosis and management of PID and in research to understand their level of awareness of AI, their perceptions of the usefulness of AI, and the major difficulties that might limit its adoption. The findings of this study can inform policy making, resource management, and strategy development for the incorporation of AI into PID care to improve patient outcomes.