Published on in Vol 3 (2024)

This is a member publication of University of Washington

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58398, first published .
Smartphone Pupillometry and Machine Learning for Detection of Acute Mild Traumatic Brain Injury: Cohort Study

Smartphone Pupillometry and Machine Learning for Detection of Acute Mild Traumatic Brain Injury: Cohort Study

Smartphone Pupillometry and Machine Learning for Detection of Acute Mild Traumatic Brain Injury: Cohort Study

Anthony J Maxin   1, 2 , BS ;   Do H Lim   1, 3 , BA ;   Sophie Kush   4 , BS ;   Jack Carpenter   5 , BS ;   Rami Shaibani   6 , MS ;   Bernice G Gulek   1 , PhD ;   Kimberly G Harmon   7 , MD ;   Alex Mariakakis   8 , PhD ;   Lynn B McGrath   4 , MD ;   Michael R Levitt   1, 3, 9, 10 , MD

1 Department of Neurological Surgery, University of Washington, Seattle, WA, United States

2 School of Medicine, Creighton University, Omaha, NE, United States

3 Stroke & Applied Neuroscience Center, University of Washington, Seattle, WA, United States

4 Department of Neurological Surgery, Weill Cornell Medicine, New York, NY, United States

5 Santa Clara University, Santa Clara, CA, United States

6 Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, United States

7 Department of Family Medicine, University of Washington, Seattle, WA, United States

8 Department of Computer Science, University of Toronto, Toronto, ON, Canada

9 Department of Radiology, University of Washington, Seattle, WA, United States

10 Department of Mechanical Engineering, University of Washington, Seattle, WA, United States

Corresponding Author:

  • Michael R Levitt, MD
  • Department of Neurological Surgery
  • University of Washington
  • 325 9th Avenue
  • Seattle, WA, 98104
  • United States
  • Phone: 1 2067449305
  • Fax: 1 2067449943
  • Email: mlevitt@uw.edu