Using Machine Learning to Improve Surgical Treatment of Children with Craniosynostosis

Pediatric craniosynostosis, a condition where two or more cranial bones fuse prematurely, restricts cranial and brain growth in children. When diagnosed, doctors typically recommend surgery with two main objectives: to remove the constraints on cranial and brain growth and to correct aesthetic malformations. However, the outcomes of these surgeries can vary significantly due to different surgical techniques employed across institutions.
In this video, Antonio R. Porras, PhD, explains how the team at Children's Hospital Colorado and the University of Colorado is creating advanced data-driven techniques, including AI methods, to enhance precision in craniosynostosis surgery planning. This approach aims to improve the understanding of cranial growth patterns and monitor post-surgical progress more effectively.
For more information from the Department of Pediatric Surgery, please visit www.childrenscolorado.org/doc...
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