CardioVision: a software platform to bring Artificial Intelligence and mixed reality to pediatric cardiology

Andreas Jahnen, Jérémie Dabin, Giuseppe Alberto Annoni, Alexandru Adrian Tantar, Bjorn Cools, Isabelle Thierry-Chef

    Research outputpeer-review

    Abstract

    Pediatric cardiology presents a unique set of challenges, where the accurate diagnosis and treatment of rare and complex conditions demand a thorough understanding of patient-specific anatomy and physiology. However, the integration of cutting-edge research and AI models into clinical practice remains a significant practical challenge. CardioVision is a novel software platform designed to bridge this gap, providing pediatric cardiologists with an easy accessible and comprehensive tool for preparing and managing challenging cases. By integrating AI-powered analytics, 3D visualization, and collaborative workflows, CardioVision enables clinicians to make more informed decisions, reduce radiation dose to the patient, and improve patient outcomes. This paper presents the CardioVision platform, highlighting its key features and functionalities, and discusses the potential CardioVision has for improving personalized medicine in pediatric cardiology.
    Original languageEnglish
    Title of host publication2024 IEEE International Conference on Bioinformatics and Biomedicine
    PublisherIEEE Computer Society
    Number of pages5
    ISBN (Electronic)979-8-3503-8622-6
    ISBN (Print)979-8-3503-8623-3
    DOIs
    StatePublished - 6 Dec 2024

    Publication series

    NameIEEE International Conference on Bioinformatics and Biomedicine (BIBM)
    PublisherIEEE
    ISSN (Print)2156-1125
    ISSN (Electronic)2156-1133

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