Zusammenfassung
Neue digitale Technologien werden auch in der Gefäßchirurgie an Bedeutung gewinnen, mit einem breiten Feld an Anwendungsgebieten. Die Simulation endovaskulärer Eingriffe kann zur Verbesserung prozedurenspezifischer Parameter führen und die Fluoroskopie- und Prozedurenzeit verkürzen. Die Anwendung der intraoperativen Navigation und Robotik ermöglicht ebenso eine Reduktion der Strahlendosis. Durch maschinelles Lernen könnte eine Risikostratifizierung und Individualisierung der Therapie stattfinden. Health-Apps ermöglichen, die Nachsorge der Patienten zu verbessern.
Abstract
New digital technologies will also gain in importance in vascular surgery. There is a wide field of potential applications. Simulation-based training of endovascular procedures can lead to improvement in procedure-specific parameters and reduce fluoroscopy and procedural times. The use of intraoperative image-guided navigation and robotics also enables a reduction of the radiation dose. Artificial intelligence can be used for risk stratification and individualization of treatment approaches. Health apps can be used to improve the follow-up care of patients.
Notes
Zertifiziert durch die Deutsche Gesellschaft für Gefäßchirurgie und Gefäßmedizin.
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S. Wolk, M. Kleemann und C. Reeps geben an, dass kein Interessenkonflikt besteht.
Für diesen Beitrag wurden von den Autoren keine Studien an Menschen oder Tieren durchgeführt. Für die aufgeführten Studien gelten die jeweils dort angegebenen ethischen Richtlinien.
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Wolk, S., Kleemann, M. & Reeps, C. Künstliche Intelligenz in der Gefäßchirurgie und Gefäßmedizin. Chirurg 91, 195–200 (2020). https://doi.org/10.1007/s00104-020-01143-5
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DOI: https://doi.org/10.1007/s00104-020-01143-5
Schlüsselwörter
- Digitale Transformation
- Navigation in der Gefäßchirurgie
- Machinelles Lernen
- Virtual Reality
- Digital Health