Abstract
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.KeywordsChronic HepatitisLiver BiopsyDown SyndromeGenetic ProgramClinical Decision SupportThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
