News-Medical.Net November 11, 2024
A team of clinicians, scientists, and engineers at Mount Sinai trained a deep learning pose-recognition algorithm on video feeds of infants in the neonatal intensive care unit (NICU) to accurately track their movements and identify key neurologic metrics.
Findings from this new artificial intelligence (AI)-based tool, published November 11 in Lancet’s eClinicalMedicine, could lead to a minimally invasive, scalable method for continuous neurologic monitoring in NICUs, providing critical real-time insights into infant health that have not been possible before.
Every year, more than 300,000 newborns are admitted to NICUs across the United States. Infant alertness is considered the most sensitive piece of the neurologic exam, reflecting integrity throughout the central nervous system. Neurologic deterioration in NICUs can happen unexpectedly and...
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