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Commentary: Machine Learning-Driven Clinical Image Analysis to Identify Craniosynostosis: A Pilot Study of Telemedicine and Clinic Patients.

Publication ,  Journal Article
Quon, JL; Grant, GA
Published in: Neurosurgery
June 1, 2022

Duke Scholars

Published In

Neurosurgery

DOI

EISSN

1524-4040

Publication Date

June 1, 2022

Volume

90

Issue

6

Start / End Page

e159 / e160

Location

United States

Related Subject Headings

  • Telemedicine
  • Pilot Projects
  • Neurology & Neurosurgery
  • Machine Learning
  • Image Processing, Computer-Assisted
  • Humans
  • Craniosynostoses
  • 5202 Biological psychology
  • 3209 Neurosciences
  • 3202 Clinical sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Quon, J. L., & Grant, G. A. (2022). Commentary: Machine Learning-Driven Clinical Image Analysis to Identify Craniosynostosis: A Pilot Study of Telemedicine and Clinic Patients. Neurosurgery, 90(6), e159–e160. https://doi.org/10.1227/neu.0000000000001943
Quon, Jennifer L., and Gerald A. Grant. “Commentary: Machine Learning-Driven Clinical Image Analysis to Identify Craniosynostosis: A Pilot Study of Telemedicine and Clinic Patients.Neurosurgery 90, no. 6 (June 1, 2022): e159–60. https://doi.org/10.1227/neu.0000000000001943.
Quon, Jennifer L., and Gerald A. Grant. “Commentary: Machine Learning-Driven Clinical Image Analysis to Identify Craniosynostosis: A Pilot Study of Telemedicine and Clinic Patients.Neurosurgery, vol. 90, no. 6, June 2022, pp. e159–60. Pubmed, doi:10.1227/neu.0000000000001943.
Journal cover image

Published In

Neurosurgery

DOI

EISSN

1524-4040

Publication Date

June 1, 2022

Volume

90

Issue

6

Start / End Page

e159 / e160

Location

United States

Related Subject Headings

  • Telemedicine
  • Pilot Projects
  • Neurology & Neurosurgery
  • Machine Learning
  • Image Processing, Computer-Assisted
  • Humans
  • Craniosynostoses
  • 5202 Biological psychology
  • 3209 Neurosciences
  • 3202 Clinical sciences