An Explainable Intervention Prediction for Trauma Patients

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 Jan 2023Publisher:ZenodoJournal:SWAT4HCLS 2023 conference ProceedingsFunded by:EC | INGENIOUS, EC | NIGHTINGALE

Authors: Vasileiou, Zoe; Meditskos, Georgios; Vrochidis, Stefanos; Bassiliades, Nick;

doi: 10.5281/zenodo.7664127 , 10.5281/zenodo.7664126

An Explainable Intervention Prediction for Trauma Patients

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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 neurosymbolic Explainable Artificial Intelligence (XAI) techniques.

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Keywords

Logic Tensor Networks, Trauma, Neurosymbolic, Ventilation

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