Smartphone pupillometry with machine learning differentiates ischemic from hemorrhagic stroke: A pilot study.

Abstract

Authors

• Anthony J Maxin
  Department of Neurological Surgery, University of Washington, Seattle, WA, USA; School of Medicine, Creighton University, Omaha, NE, USA. Electronic address: anthonymaxin@creighton.edu.
• Bernice G Gulek
  Department of Neurological Surgery, University of Washington, Seattle, WA, USA. Electronic address: gulekb@uw.edu.
• Do H Lim
  Department of Neurological Surgery, University of Washington, Seattle, WA, USA. Electronic address: dolim@uw.edu.
• Samuel Kim
  Canary Speech LLC, Provo, Utah, USA.
• Rami Shaibani
  Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA. Electronic address: rshaiba@gmail.com.
• Graham M Winston
  Department of Neurological Surgery, Weill Cornell Medicine, New York, NY, USA. Electronic address: gmw2002@nyp.org.
• Lynn B McGrath
  Department of Neurosurgery, University of Washington, Seattle, Washington, USA.
• Alex Mariakakis
  Department of Computer Science, University of Toronto, Toronto, ON, Canada. Electronic address: mariakakis@cs.toronto.edu.
• Isaac J Abecassis
  Department of Neurosurgery, University of Louisville, Louisville KY, USA.
• Michael R Levitt
  Department of Neurological Surgery, University of Washington, Seattle, WA, USA; Departments of Radiology, Neurology, Mechanical Engineering, and Stroke & Applied Neuroscience Center, University of Washington, Seattle, WA, USA. Electronic address: mlevitt@uw.edu.

Keywords

External Resources