Machine-learning prediction of self-care activity by grip strengths of both hands in poststroke hemiplegia

To investigate the relationships between grip strengths and self-care activities in stroke patients using a non-linear support vector machine (SVM).Overall, 177 inpatients with poststroke hemiparesis were enrolled. Their grip strengths were measured using the Jamar dynamometer on the first day of re...

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Veröffentlicht in:	Medicine (Baltimore) 2020-03, Vol.99 (11), p.e19512-e19512
Hauptverfasser:	Suzuki, Makoto, Sugimura, Seiichiro, Suzuki, Takako, Sasaki, Shotaro, Abe, Naoto, Tokito, Takahide, Hamaguchi, Toyohiro
Format:	Artikel
Sprache:	eng
Schlagworte:	Aged Disability Evaluation Female Hand Strength Humans Machine Learning Male Observational Study Paresis - physiopathology Paresis - rehabilitation Patient Discharge Predictive Value of Tests Self Care Stroke Rehabilitation
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