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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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI AG
2026-03-01
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| Col·lecció: | Diagnostics |
| Matèries: | |
| Accés en línia: | https://www.mdpi.com/2075-4418/16/6/954 |
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