Interpretable Machine Learning for Emergency Department Triage: Clinical Insights from 133,198 Patients Using the Korean Triage and Acuity Scale (KTAS)

<b>Background/Objectives:</b> Emergency room severity classification (KTAS) is essential for patient safety but has limitations due to its reliance on subjective judgment. Existing machine learning models have not been trusted in clinical settings due to their opaque ‘black box’ nature in decision-m...

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Bibliografski detalji

Glavni autori:	MyoungJe Song, Jongsun Kim, Eun-Chul Jang, SoonChan Kwon
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2026-03-01
Serija:	Diagnostics
Teme:	emergency department triage Korean triage and acuity scale (KTAS) decision-making machine learning explainable artificial intelligence (XAI)
Online pristup:	https://www.mdpi.com/2075-4418/16/6/954
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