Improvement of predictive accuracies of functional outcomes after subacute stroke inpatient rehabilitation by machine learning models

OBJECTIVES: Stepwise linear regression (SLR) is the most common approach to predicting activities of daily living at discharge with the Functional Independence Measure (FIM) in stroke patients, but noisy nonlinear clinical data decrease the predictive accuracies of SLR. Machine learning is gaining a...

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Detalles Bibliográficos
Autores principales: Miyazaki, Yuta, Kawakami, Michiyuki, Kondo, Kunitsugu, Tsujikawa, Masahiro, Honaga, Kaoru, Suzuki, Kanjiro, Tsuji, Tetsuya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10218720/
https://www.ncbi.nlm.nih.gov/pubmed/37235575
http://dx.doi.org/10.1371/journal.pone.0286269

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10218720/
https://www.ncbi.nlm.nih.gov/pubmed/37235575
http://dx.doi.org/10.1371/journal.pone.0286269

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