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A machine learning approach for predicting post-stroke apha..:
, In:
Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments
,
Gu, Yiwen
;
Bahrani, Murtadha
;
Billot, Anne
... - p. 1-9 , 2020
Link:
https://dl.acm.org/doi/10.1145/3389189.3389204
RT T1
Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments
: T1
A machine learning approach for predicting post-stroke aphasia recovery : a pilot study
UL https://suche.suub.uni-bremen.de/peid=acm-3389204&Exemplar=1&LAN=DE A1 Gu, Yiwen A1 Bahrani, Murtadha A1 Billot, Anne A1 Lai, Sha A1 Braun, Emily J. A1 Varkanitsa, Maria A1 Bighetto, Julia A1 Rapp, Brenda A1 Parrish, Todd B. A1 Caplan, David A1 Thompson, Cynthia K. A1 Kiran, Swathi A1 Betke, Margrit PB ACM YR 2020 K1 aphasia K1 machine learning K1 recovery K1 stroke K1 Computing methodologies SP 1 OP 9 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3389189.3389204 DO https://dl.acm.org/doi/10.1145/3389189.3389204 SF ELIB - SuUB Bremen
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