Abstract
In this paper we argue that Neuro-Symbolic AI (NeSy-AI) should be applied for patient monitoring. In this context, we introduce patient monitoring as a special case of Human Activity Recognition and derive concrete requirements for this application area. We then present a process architecture and discuss why NeSy-AI should be applied for patient monitoring. To further support our argumentation, we show how NeSy-AI can help to overcome certain technical challenges that arise from this application area.
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We want to thank GWA Hygiene for providing us with the sensors as well as the additional infrastructure which is necessary for a project like this.
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Fenske, O., Bader, S., Kirste, T. (2025). Neuro-symbolic Artificial Intelligence for Patient Monitoring. In: Meo, R., Silvestri, F. (eds) Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2023. Communications in Computer and Information Science, vol 2136. Springer, Cham. https://doi.org/10.1007/978-3-031-74640-6_2
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DOI: https://doi.org/10.1007/978-3-031-74640-6_2
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