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Digitale Verfahren verändern die operative Versorgung in der Mund-, Kiefer- und Gesichtschirurgie grundlegend. Der Vortrag beleuchtet die Anwendung künstlicher Intelligenz zur automatisierten Bildanalyse sowie den Einsatz 3D-gefertigter patientenspezifischer Implantate bei komplexen Rekonstruktionen. Voraussetzung für valide KI-gestützte Planung ist eine standardisierte, qualitativ hochwertige Datengrundlage. Die MKG-Chirurgie erweist sich dabei als methodisches Innovationsfeld mit hoher klinischer Relevanz, das interdisziplinär Maßstäbe für eine individualisierte Patientenversorgung setzt.

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Matricelf is pioneering the first autologous neural tissue implant designed to restore motor and sensory function in patients with chronic spinal cord injury. By leveraging patient-derived induced pluripotent stem cells (iPSCs) and advanced 3D-engineered micro-tissues, the company creates living neural grafts uniquely tailored to each individual. This approach bridges regenerative medicine and surgical innovation, offering a one-time curative treatment where only palliative solutions exist today. The technology has demonstrated safety and efficacy in preclinical models, setting the stage for first-in-human trials. With its personalized and scalable strategy, Matricelf aims to transform spinal cord injury from a lifelong disability into a condition with a therapeutic pathway toward recovery.

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In the form of a case-based guide, this presentation addresses, for the first time, questions regarding the use of new AI-supported technologies in healthcare from legal, sociological, ethical, and epistemological perspectives. Using commentary on a realistic patient journey scenario, the presentation offers recommendations for the responsible use of AI in medicine.

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Hospitals manage large volumes of data but still face challenges with time-consuming documentation and disconnected systems. In this talk, I’ll explore how practical expert systems can turn structured knowledge into everyday support for clinicians. I will also present an early-stage prototype that automates clinical notes, extracts data from documents, and connects information across hospital applications. These tools aim to simplify clinical work and create a foundation for more connected, efficient healthcare.

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