Autonomous diagnosis of pediatric cutaneous vascular anomalies using a convolutional neural network.

Journal: International journal of pediatric otorhinolaryngology
Published Date:

Abstract

OBJECTIVES: Design and validate a novel handheld device for the autonomous diagnosis of pediatric vascular anomalies using a convolutional neural network (CNN).

Authors

  • Palak Patel
    Louisiana State University Health Sciences Center, Department of Otolaryngology, Head and Neck Surgery, New Orleans, Louisiana, USA. Electronic address: ppat13@lsuhsc.edu.
  • Katelyn Ragland
    University of Arkansas for Medical Sciences, Department of Otolaryngology, Head and Neck Surgery, Little Rock, Arkansas, USA. Electronic address: kmragland@uams.edu.
  • Brianna Robertson
    Louisiana State University School of Engineering, Baton Rouge, Louisiana, USA. Electronic address: brobe86@lsu.edu.
  • Gabriel Ragusa
    Louisiana State University School of Engineering, Baton Rouge, Louisiana, USA. Electronic address: gragus2@lsu.edu.
  • Christine Wiley
    Louisiana State University School of Engineering, Baton Rouge, Louisiana, USA. Electronic address: cwile12@lsu.edu.
  • Jacob Miller
    Louisiana State University School of Engineering, Baton Rouge, Louisiana, USA. Electronic address: jmil266@lsu.edu.
  • Robert Jullens
    Louisiana State University School of Engineering, Baton Rouge, Louisiana, USA. Electronic address: rjulle3@lsu.edu.
  • Michael Dunham
    Louisiana State University Health Sciences Center, Department of Otolaryngology, Head and Neck Surgery, New Orleans, Louisiana, USA. Electronic address: mdunha@lsuhsc.edu.
  • Gresham Richter
    University of Arkansas for Medical Sciences, Department of Otolaryngology, Head and Neck Surgery, Little Rock, Arkansas, USA. Electronic address: gtrichter@uams.edu.