Leveraging AI and Machine Learning for Next-Generation Clinical Decision Support Systems (CDSS)

Abstract

Missed diagnoses and medication errors are significant risks in healthcare, leading to increased patient morbidity and mortality. Traditional Clinical Decision Support Systems (CDSS) rely on static, predefined rules, limiting their adaptability to personalized patient care. This chapter explores how integrating Artificial Intelligence (AI) and Machine Learning (ML) can revolutionize CDSS, driving next-generation systems. By analyzing clinical datasets in real time, AI and ML enable personalized insights that enhance diagnostic accuracy, optimize treatment recommendations, improve risk stratification, and streamline workflows. These advancements promise better patient outcomes, informed clinical decisions, and reduced costs. The chapter also addresses challenges like data quality, explainability, regulatory compliance, and ethics, proposing strategies for overcoming these. Through collaboration and research, AI and ML can transform CDSS into foundational healthcare elements, fostering personalized, data-driven, and efficient patient care.

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