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Machine Learning Classification to Identify the Stage of Brain-Computer Interface Therapy for Stroke Rehabilitation Using Functional Connectivity.
Mohanty, Rosaleena; Sinha, Anita M; Remsik, Alexander B; Dodd, Keith C; Young, Brittany M; Jacobson, Tyler; McMillan, Matthew; Thoma, Jaclyn; Advani, Hemali; Nair, Veena A; Kang, Theresa J; Caldera, Kristin; Edwards, Dorothy F; Williams, Justin C; Prabhakaran, Vivek.
Afiliación
  • Mohanty R; Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States.
  • Sinha AM; Department of Electrical Engineering, University of Wisconsin-Madison, Madison, WI, United States.
  • Remsik AB; Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States.
  • Dodd KC; Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.
  • Young BM; Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States.
  • Jacobson T; Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, United States.
  • McMillan M; Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States.
  • Thoma J; Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.
  • Advani H; Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, United States.
  • Nair VA; Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States.
  • Kang TJ; Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States.
  • Caldera K; Deparment of Psychology, University of Wisconsin-Madison, Madison, WI, United States.
  • Edwards DF; Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States.
  • Williams JC; Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States.
  • Prabhakaran V; Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States.
Front Neurosci ; 12: 353, 2018.
Article en En | MEDLINE | ID: mdl-29896082
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Neurosci Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Neurosci Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza