Clinical Decision Support Systems (CDSS) are integral tools in modern healthcare, designed to assist clinicians by providing patient-specific recommendations based on vast medical data and knowledge. The advent of Artificial Intelligence (AI) has significantly enhanced CDSS, enabling sophisticated predictive analytics, early detection of complications, and personalized interventions. AI techniques like machine learning, natural language processing, and deep learning play crucial roles in refining CDSS functionality. However, challenges such as data quality, AI transparency, and clinician trust hinder widespread adoption. Future trends focus on improving AI integration in CDSS through better data representation, automation, and ethical considerations. This paper investigates the fundamental aspects of CDSS, the applications of AI in healthcare, and the challenges and future directions for AI-driven CDSS.
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Mukamurera P. Nyiramana (2024) studied this question.
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