Logistic regression analysis and machine learning for predicting post-stroke gait independence: a retrospective study-Reference-Cited by-同舟云学术

Logistic regression analysis and machine learning for predicting post-stroke gait independence: a retrospective study

Published:2024-09-11 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Miyazaki Yuta,Kawakami Michiyuki,Kondo Kunitsugu,Hirabe Akiko,Kamimoto Takayuki,Akimoto Tomonori,Hijikata Nanako,Tsujikawa Masahiro,Honaga Kaoru,Suzuki Kanjiro,Tsuji Tetsuya

Funder

Japan Society for the Promotion of Science

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-72206-4.pdf

Reference35 articles.

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3. Kwakkel, G. et al. Motor rehabilitation after stroke: European Stroke Organisation (ESO) consensus-based definition and guiding framework. Eur. Stroke J. 8, 880–894. https://doi.org/10.1177/23969873231191304 (2023).

4. Deutsch, A. et al. Poststroke rehabilitation: Outcomes and reimbursement of inpatient rehabilitation facilities and subacute rehabilitation programs. Stroke 37, 1477–1482. https://doi.org/10.1161/01.STR.0000221172.99375.5a (2006).

5. Stinear, C. M., Smith, M. C. & Byblow, W. D. Prediction tools for stroke rehabilitation. Stroke 50, 3314–3322. https://doi.org/10.1161/strokeaha.119.025696 (2019).