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Poster
in
Affinity Event: Muslims in ML

Explainable, Generalizable and Responsible AI Model to Triage Emergency Patients

Jemal Abdulkadir Fulli · Berihun Tsega Alemayehu · Omer Yasin · Abubeker Ahmed · Muhammed Sualih

Keywords: [ triage ] [ emergency healthcare ] [ achine learning ] [ responsible AI ]


Abstract:

Triage helps to deliver the right level of emergency healthcare at the right time for the right person using the right resources. However, triage is vulnerable to mis-triage which causes delayed treatment, poor healthcare outcomes and ED overcrowding. This study, hence, aimed to develop an explainable, generalizable and responsible AI model that assists triage nurses. We identify the most important predictors, measure the order, direction, and effects of important predictors across triage levels, and quantify the minimum information required to develop a generalizable triage model.

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