Multiple imputation integrated to machine learning: predicting post-stroke recovery of ambulation after intensive inpatient rehabilitation

Multiple imputation integrated to machine learning: predicting post-stroke recovery of ambulation after intensive inpatient rehabilitation

Abstract Good data quality is vital for personalising plans in rehabilitation. Machine learning (ML) improves prognostics but integrating it with Multiple Imputation (MImp) for dealing missingness is an unexplored field. This work aims to provide post-stroke ambulation prognosis, integrating MImp wi...

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Bibliographic Details
Main Authors: Alice Finocchi, Silvia Campagnini, Andrea Mannini, Stefano Doronzio, Marco Baccini, Bahia Hakiki, Donata Bardi, Antonello Grippo, Claudio Macchi, Jorge Navarro Solano, Michela Baccini, Francesca Cecchi
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Ambulation
Machine learning
Multiple imputation
Prediction
Rehabilitation
Stroke
Online Access:https://doi.org/10.1038/s41598-024-74537-8
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