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An analytical evaluation of imputation methods for enhancing cardiac care data integrity

Electronic Health Records (EHRs) are comprised of digitally stored patient and population health data. Unfortunately, EHRs are often far from complete, and these incomplete health records are referred to as missingness. Missingness in EHRs is a hindrance factor in utilizing Machine Learning (ML) for...

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Autores principales: Rajarajeswari Ganesan, Carlijn M.A. Buck, Chang Sun, Marcel van’t Veer, Lukas R.C. Dekker, Frans N. van de Vosse, Wouter Huberts
Formato: Artigo
Lenguaje:Inglês
Publicado: Elsevier 2026-06-01
Colección:Healthcare Analytics
Materias:
Machine Learning
Missing data
Electronic Health Records
Data imputation
Clinical studies
Cardiovascular diseases
Acceso en línea:http://www.sciencedirect.com/science/article/pii/S2772442526000067
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