CardioVision: A Software Platform to Bring Artificial Intelligence and Mixed Reality to Pediatric Cardiology
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.
Authors
- Björn Cools (ORCID: https://orcid.org/0000-0003-3633-4216)
- G Annoni (ORCID: https://orcid.org/0000-0003-2059-2421)
- Andréas Jahnen (ORCID: https://orcid.org/0000-0002-7379-5145)
- Isabelle Thierry-Chef (ORCID: https://orcid.org/0000-0001-6304-2783)
- Alexandru Tantar
- Jérémie Dabin (ORCID: https://orcid.org/0000-0002-9462-5807)
Institutions
- Luxembourg Institute of Science and Technology (LU)
- Belgian Nuclear Research Centre (BE)
- Ospedale Regina Margherita (IT)
- Barcelona Institute for Global Health (ES)
- KU Leuven (BE)
Publication Details
- Published
- 2024-12-03
- DOI
- https://doi.org/10.1109/bibm62325.2024.10822130
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.24