Functional Near-Infrared Spectroscopy Combined with Machine Learning for Exploratory Classification of Autism Spectrum Disorder in Young Children.
Overall classification performance was modest; none of the evaluated classifiers demonstrated statistically significant above-chance performance in the permutation tests, and the fNIRS features did not demonstrate statistically significant incremental predictive value beyond age and sex.