APPLICATION OF BUSINESS INTELLIGENCE METHODS AND TECHNIQUES IN THE ANALYSIS OF TREATMENT OF PATIENTS WITH DIABETES

Diabetes is a well known medical condition characterized by elevated blood glucose levels that needs personalized treatment and continuous monitoring for patients. Recent advancements in artificial intelligence (AI) have significantly transformed how we treat diabetes. This paper examines the application of business intelligence (BI) methods and techniques in optimizing patient care for diabetes. We will begin by exploring the theoretical foundation of diabetes as a disease, its types, complications, and global statistics. The study highlights how BI in combination with AI can be used to process large datasets, forecast outcomes, and personalize treatments. With carefully analyzing patient data such as glucose levels, physical activity, and diet, BI methods can identify risk factors, early intervention strategies, and more accurate diagnoses. Moreover, the use of BI supports the development of dynamic, real-time dashboards that allow healthcare professionals to monitor patient progress and adherence to treatment plans efficiently. The integration of AI-driven algorithms within BI platforms enhances the predictive capability for detecting early signs of complications. This research also emphasizes the operational and cost advantages of BI in improving patient monitoring in clinical settings. The insights underline the importance of BI in healthcare systems, reducing costs, and ensuring better health outcomes for diabetes patients.