Artificial Intelligence-Clinical Decision Support Systems: Integrating Intelligent Evidence Retrieval with Advanced AI for Personalized Healthcare

Abstract

In recent years, artificial intelligence and big data have increasingly influenced healthcare, contributing to the development of clinical decision support systems (CDSS). This paper presents a framework for an Artificial Intelligence-CDSS(AI-CDSS) that retrieves and summarizes recent medical literature to build a continuously updated knowledge base. The goal is to provide clinicians with the latest evidence for informed decision-making. The framework uses natural language processing and graph neural networks to convert unstructured literature into structured knowledge graphs, while integrating multimodal data to generate clinical recommendations. These recommendations are personalized and interpretable, facilitated by Transformer models. The paper discusses the challenges encountered by the framework, its role in precision medicine, and its potential applications in clinical decision-making, as well as future directions for improving data integration and decision models.

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