Nailfold capillaroscopy and deep learning in diabetes.

Journal: Journal of diabetes
PMID:

Abstract

OBJECTIVE: To determine whether nailfold capillary images, acquired using video capillaroscopy, can provide diagnostic information about diabetes and its complications.

Authors

  • Reema Shah
    Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada.
  • Jeremy Petch
    Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada.
  • Walter Nelson
    Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.
  • Karsten Roth
  • Michael D Noseworthy
    McMaster Integrative Neuroscience Discovery and Study (MiNDS), McMaster University, 1280 Main St. W., Hamilton, Ontario L8S 4K1, Canada; Department of Electrical and Computer Engineering, McMaster University, 1280 Main St. W., Hamilton, Ontario L8S 4K1, Canada; McMaster School of Biomedical Engineering, McMaster University, 1280 Main St. W., Hamilton, Ontario L8S 4K1, Canada; Imaging Research Centre, St. Joseph's Healthcare Hamilton, 50 Charlton Ave. E., Hamilton, Ontario L8N 4A6, Canada.
  • Marzyeh Ghassemi
    Electrical Engineering and Computer Science, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States.
  • Hertzel C Gerstein
    Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada.