Distributed Intrinsic Functional Connectivity Patterns Predict Diagnostic Status in Large Autism Cohort

@article{Jahedi2017DistributedIF,
  title={Distributed Intrinsic Functional Connectivity Patterns Predict Diagnostic Status in Large Autism Cohort},
  author={Afrooz Jahedi and Chanond A. Nasamran and Brian Faires and Juanjuan Fan and Ralph-Axel M{\"u}ller},
  journal={Brain connectivity},
  year={2017},
  volume={7 8},
  pages={515-525}
}
Diagnosis of autism spectrum disorder (ASD) currently relies on behavioral observations because brain markers are unknown. Machine learning approaches can identify patterns in imaging data that predict diagnostic status, but most studies using functional connectivity MRI (fcMRI) data achieved only modest accuracies of 60-80%. We used conditional random… CONTINUE READING