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June 10, 2020SHILAP Revista de lepidopterologíaOpen Access

Inpatient stroke rehabilitation: prediction of clinical outcomes using a machine-learning approach

Yaar Harari Megan K. O’Brien Richard L. Lieber Arun Jayaraman

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Abstract

The models presented in this study could help clinicians and researchers to predict the discharge scores of clinical outcomes for individuals enrolled in an inpatient stroke rehabilitation program that adheres to U.S. Medicare standards.

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Cite This Study

Harari et al. (2020) studied this question.

synapsesocial.com/papers/69db547a7a67537a8ba3d266 https://doi.org/10.1186/s12984-020-00704-3

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Evidence-based stroke rehabilitation: an expanded guidance document from the european stroke organisation (ESO) guidelines for management of ischaemic stroke and transient ischaemic attack 2008Cost-Effectiveness Analysis · 2009 · 201 citations
2Comparison of the psychometric characteristics of the functional independence measure, 5 item Barthel index, and 10 item Barthel index in patients with strokeOriginal Research · 2002 · 416 citations
3Outcome Measures for Individuals With Stroke: Process and Recommendations From the American Physical Therapy Association Neurology Section Task ForceSystematic Review · 2013 · 212 citations
4The TWIST Algorithm Predicts Time to Walking Independently After StrokeDiagnostic Study · 2017 · 131 citations
5A systematic review of studies reporting multivariable models to predict functional outcomes after post-stroke inpatient rehabilitationPrognostic Study · 2014 · 169 citations

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Development and Validation of a Predictive Model for Functional Outcome After Stroke Rehabilitation2017
Measure of Functional Independence Dominates Discharge Outcome Prediction After Inpatient Rehabilitation for Stroke2015
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