AI-Driven Clinical Decision Support Systems Enhance Healthcare Efficiency
Clinical decision support systems (CDSS) are increasingly being integrated into healthcare to assist clinicians and patients in making informed decisions regarding diagnosis, treatment, and care management. These systems link individual patient data with organized medical knowledge to generate patient-specific assessments or recommendations. CDSS can be knowledge-based, using encoded rules and clinical guidelines, or data-driven, employing statistical and machine learning models trained on large datasets to identify patterns and predict outcomes. The effectiveness of these systems depends on the quality and completeness of the underlying data, their integration into clinical workflows, and the trust and acceptance of users. Research in this area focuses on the application of artificial intelligence to enhance efficiency and support clinical judgment, as well as on factors affecting data quality in health facilities and quality-improvement strategies in care delivery. 
