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Use of Machine Learning Classifiers and Sensor Data to Detect Neurological Deficit in Stroke Patients.

Eunjeong ParkSeo Young SongHyo Suk Nam
Published in: Journal of medical Internet research (2017)
Sensors and machine learning methods can reliably detect stroke signs and quantify proximal arm weakness. Our proposed solution will facilitate pervasive monitoring of stroke patients.
Keyphrases
  • machine learning
  • big data
  • artificial intelligence
  • atrial fibrillation
  • electronic health record
  • deep learning
  • cerebral ischemia
  • low cost
  • blood brain barrier
  • brain injury