Image processing and machine learning for telehealth craniosynostosis screening in newborns.

Journal: Journal of neurosurgery. Pediatrics

Published Date: Mar 19, 2021

Abstract

OBJECTIVE: The authors sought to evaluate the accuracy of a novel telehealth-compatible diagnostic software system for identifying craniosynostosis within a newborn (< 1 year old) population. Agreement with gold standard craniometric diagnostics was also assessed.

Authors

Markus J Bookland

1Division of Neurosurgery, Connecticut Children's, Hartford.
Edward S Ahn

3Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota.
Petronella Stoltz

1Division of Neurosurgery, Connecticut Children's, Hartford.
Jonathan E Martin

1Division of Neurosurgery, Connecticut Children's, Hartford.

Keywords

Cephalometry Craniosynostoses Female Humans Image Interpretation, Computer-Assisted Infant, Newborn Machine Learning Male Mass Screening Software Telemedicine

External Resources

View on PubMed Access via DOI PubMed (33740758)

Image processing and machine learning for telehealth craniosynostosis screening in newborns.

Abstract

Authors

Keywords

External Resources

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