Open Access
ARTICLE
AI-Enhanced Clinical Decision Support Systems: Improving Diagnostic Accuracy and Reducing Medical Errors in Tertiary Healthcare Settings
Issue Vol. 1 No. 01 (2025): Volume 01 , Issue 01 Oct 2025 --- Section Articles --- Published Date: 2025-10-01
Abstract
Clinical Decision Support Systems (CDSS) have become integral to modern healthcare, particularly in tertiary hospitals where patient complexity and diagnostic demands are significantly higher. The introduction of Artificial Intelligence (AI)-enhanced CDSS offers transformative potential by improving diagnostic accuracy, reducing medical errors, and strengthening clinician decision-making. This study examines the design, deployment, and evaluation of AI-driven CDSS in tertiary healthcare environments. It highlights the use of machine learning (ML), natural language processing (NLP), deep learning diagnostic tools, and predictive risk algorithms. Through clinical workflow analysis, case studies, model validation metrics, and stakeholder perceptions, the study demonstrates that AI-CDSS can reduce diagnostic errors by up to 40% and improve clinician confidence, while also identifying key challenges such as data quality, algorithm bias, and clinician training gaps. The findings provide actionable strategies for optimizing AI-CDSS integration to enhance patient safety and healthcare quality.
Article Cover Image
