Dresden 2026 – wissenschaftliches Programm
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HL: Fachverband Halbleiterphysik
HL 22: Biocompatible Organic Semiconductors
HL 22.4: Vortrag
Mittwoch, 11. März 2026, 10:15–10:30, POT/0006
Obtaining In-Vivo Data for AI Applications Using Implantable Biocompatible Materials — •Finn Jaekel1, Richard Kantelberg1, Hans Kleemann1, Daniel Freund2, Julia Henne2, Dennis Wahl2, Eberhard Grambow3, Sebastian Hinz2, Clemens Schafmayer2, Jochen Hampe4, and Karl Leo1 — 1Institut für Angewandte Photophysik, Technische Universität Dresden, Dresden, Germany — 2Klinik und Poliklinik für Allgemeine Chirurgie, Thorax, Gefäß- und Transplantationschirurgie, Universitätsmedizin Rostock, Rostock, Germany — 3Klinik für Herz-, Thorax- und Gefäßchirurgie (HTG), Universitätsmedizin Göttingen, Göttingen, Germany — 4Universitätsklinikum Carl Gustav Carus Dresden, Dresden, Germany
Artificial intelligence can be of great use in biomedical applications, especially when implemented in implantable hardware solutions. However, robust, biomedical AI applications crucially depend on real, high-quality, physiological training and input datasets, which are scarce in practice. In this presentation, we provide a prototypical use-case scenario by demonstrating in-vivo impedance measurements in a porcine small-intestinal anastomosis using printed, fully biocompatible organic sensors. Ischemia was induced locally, and manual evaluation shows a characteristic signature in the recorded impedance spectra, confirming that the system captures physiologically relevant data. This positions the technology in a realistic sensor to AI analysis pipeline, where automated detection of ischemia can be used to create an early warning system of anastomotic failure.
Keywords: Biosensors; In-Vivo; Impedance Sensing