Neurosurgery
-
The authors have developed pretrained machine learning (ML) models to evaluate neonatal head shape deformities using top-down and facial orthogonal photographs of the patient's head. In previous preliminary analysis, this approach was tested with images from an open-source data bank. ⋯ Machine learning-driven image analysis represents a promising strategy for the identification of craniosynostosis in a real-world practice setting. This approach has potential to reduce the need for imaging and facilitate referral by primary care providers.
-
Despite spinal cord stimulation's (SCS) proven efficacy, failure rates are high with no clear understanding of which patients benefit long term. Currently, patient selection for SCS is based on the subjective experience of the implanting physician. ⋯ This combined unsupervised-supervised learning approach yielded high predictive performance, suggesting that advanced ML-derived approaches have potential to be used as a functional clinical tool to improve long-term SCS outcomes. Further studies are needed for optimization and external validation of these models.