Using Computational Intelligence to Develop Intelligent Clinical Decision Support Systems

Clinical Decision Support Systems have the potential to optimize medical decisions, improve medical care, and reduce costs. An effective strategy to reach these goals is by transforming conventional Clinical Decision Support in Intelligent Clinical Decision Support, using knowledge discovery in data and computational intelligence tools. In this paper we used genetic programming and decision trees. Adaptive Intelligent Clinical Decision Support have also the capability of self-modifying their rules set, through supervised learning from patients data. Intelligent and Adaptive Intelligent Clinical Decision Support represent an essential step toward clinical research automation too, and a stronger foundation for evidence-based medicine. We proposed a methodology and related concepts, and analyzed the advantages of transforming conventional Clinical Decision Support in intelligent, adaptive Intelligent Clinical Decision Support. These are illustrated with a number of our results in liver diseases and prostate cancer, some of them showing the best published performance.

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