Interpretable machine learning approach for optimizing hospice care predictions using health assessment data

Abstract Background Determining the appropriate end-of-life (EOL) care model within a short time frame is challenging and requires extensive experience. To the best of our knowledge, no studies have developed automatic systems for identifying the hospice care models: hospice home (HHC), inpatient (H...

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Detaylı Bibliyografya
Asıl Yazarlar:	Shih-Yu Cho, Wei-Shu Lai, Jui-Hung Tsai, Peng-Chan Lin, Hsin-Hung Chou
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	BMC 2025-11-01
Seri Bilgileri:	BMC Medical Informatics and Decision Making
Konular:	Machine learning Knowledge distillation Hospice care services Health assessment data Clinical decision
Online Erişim:	https://doi.org/10.1186/s12911-025-03289-w
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Interpretable machine learning approach for optimizing hospice care predictions using health assessment data

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