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Machine learning in predicting outcomes for stroke patients following rehabilitation treatment: A systematic review.

Zu W, Huang X, Xu T, Du L, Wang Y, Wang L, Nie W. Zu W, et al. PLoS One. 2023 Jun 28;18(6):e0287308. doi: 10.1371/journal.pone.0287308. eCollection 2023. PLoS One. 2023. PMID: 37379289 Free PMC article.

Regression-based prognostic models for functional independence after postacute brain injury rehabilitation are not transportable: a systematic review.

Pommerich UM, Stubbs PW, Eggertsen PP, Fabricius J, Nielsen JF. Pommerich UM, et al. J Clin Epidemiol. 2023 Apr;156:53-65. doi: 10.1016/j.jclinepi.2023.02.009. Epub 2023 Feb 9. J Clin Epidemiol. 2023. PMID: 36764467 Free article. Review.

Development and Validation of a Predictive Model for Functional Outcome After Stroke Rehabilitation: The Maugeri Model.

Scrutinio D, Lanzillo B, Guida P, Mastropasqua F, Monitillo V, Pusineri M, Formica R, Russo G, Guarnaschelli C, Ferretti C, Calabrese G. Scrutinio D, et al. Stroke. 2017 Dec;48(12):3308-3315. doi: 10.1161/STROKEAHA.117.018058. Epub 2017 Oct 19. Stroke. 2017. PMID: 29051222

Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry.

Lin CH, Hsu KC, Johnson KR, Fann YC, Tsai CH, Sun Y, Lien LM, Chang WL, Chen PL, Lin CL, Hsu CY; Taiwan Stroke Registry Investigators. Lin CH, et al. Comput Methods Programs Biomed. 2020 Jul;190:105381. doi: 10.1016/j.cmpb.2020.105381. Epub 2020 Feb 1. Comput Methods Programs Biomed. 2020. PMID: 32044620 Free PMC article.

Machine learning methods for functional recovery prediction and prognosis in post-stroke rehabilitation: a systematic review.

Campagnini S, Arienti C, Patrini M, Liuzzi P, Mannini A, Carrozza MC. Campagnini S, et al. J Neuroeng Rehabil. 2022 Jun 3;19(1):54. doi: 10.1186/s12984-022-01032-4. J Neuroeng Rehabil. 2022. PMID: 35659246 Free PMC article. Review.

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