Deep Learning for Automating the Organization of Institutional Dermatology Image Stores

Michael Z. Wang, Nneka I. Comfere, Dennis H. Murphree

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

A common challenge faced by researchers associated with healthcare institutions is that data of interest are often contained in electronic medical informatics systems that are centered on optimizing clinician/clinician and patient/clinician communication. While this focus naturally enhances the primary goal of care delivery, it is often suboptimal for secondary research purposes. For example at our institution while it is easy for a clinician to view images associated with a specific patient visit, it remains a challenge for an investigator to assemble a cohort of specific images in order to further research objectives. In order to address this important optimization gap we have developed a system for automated image categorization based on a deep neural network. This image classifier organizes the contents of an electronic health record system in a manner which is more amenable to further research by specifically dividing all available images into a lexicon of subclasses. While the current study is focused on dermatology-related images collected by a combined primary and tertiary care center, we expect similar approaches to aid a variety of institutions and clinical specialties.

Original languageEnglish (US)
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4479-4482
Number of pages4
ISBN (Electronic)9781538613115
DOIs
StatePublished - Jul 2019
Event41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 - Berlin, Germany
Duration: Jul 23 2019Jul 27 2019

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
CountryGermany
CityBerlin
Period7/23/197/27/19

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint Dive into the research topics of 'Deep Learning for Automating the Organization of Institutional Dermatology Image Stores'. Together they form a unique fingerprint.

Cite this