May 13, 2024, 4:41 a.m. | Fengyi Gao, Xingyu Zhang, Sonish Sivarajkumar, Parker Denny, Bayan Aldhahwani, Shyam Visweswaran, Ryan Shi, William Hogan, Allyn Bove, Yanshan Wang

cs.LG updates on

arXiv:2405.05993v1 Announce Type: new
Abstract: In this study, we utilized statistical analysis and machine learning methods to examine whether rehabilitation exercises can improve patients post-stroke functional abilities, as well as forecast the improvement in functional abilities. Our dataset is patients' rehabilitation exercises and demographic information recorded in the unstructured electronic health records (EHRs) data and free-text rehabilitation procedure notes. We collected data for 265 stroke patients from the University of Pittsburgh Medical Center. We employed a pre-existing natural language processing …

abstract analysis arxiv cs.lg dataset electronic electronic health records forecast functional health improvement information machine machine learning patients precision records statistical stroke study type

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