You might also read
Articles linked to this work by shared authors, journal, and citation graph.
Updated: May 10, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Payton K Grande1, Christen M Holder2, Billy D Holcombe3,4
1University of Tennessee Health Science Center, College of Medicine, Memphis, Tennessee, USA.
Craniosynostosis impacts neurocognitive development, but standardized screening is lacking. This study recommends free, low-cost tools for early detection of developmental risks in affected children.
Area of Science:
Background:
Purpose of the Study:
Main Methods:
Main Results:
Conclusions: