An Explainable Intervention Prediction for Trauma Patients

Z. Vasileiou, G. Meditskos, S. Vrochidis, N. Bassiliades, "An Explainable Intervention Prediction for Trauma Patients", Proc. 14th International Semantic Web Applications and Tools for Health Care and Life Sciences Conference (SWAT4HCLS), Basel, Switzerland, 13-16 Feb 2023, CEUR Workshop Proceedings, Vol. 2956.

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Author(s): Z. Vasileiou, G. Meditskos, S. Vrochidis, N. Bassiliades

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Appeared In: Proc. 14th International Semantic Web Applications and Tools for Health Care and Life Sciences Conference (SWAT4HCLS), Basel, Switzerland, 13-16 Feb 2023, CEUR Workshop Proceedings, Vol. 2956.

Keywords: Trauma, Ventilation, Neurosymbolic, Explainability, Logic Tensor Networks

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2023, Bassiliades, Meditskos, Vasileiou, Vrochidis

Abstract: Trauma patients are commonly severely injured people that require systematic evaluation and rapid response. This paper presents work in progress for an explainable, late fusion and Deep Learning-based prediction system for interventions in Intensive Care Units (ICU) by employing neurosumbolic Explainable Artificial Intelligence (XAI) techniques.