Resting state functional magnetic resonance imaging and neural network classified autism and control

@article{Iidaka2015RestingSF,
  title={Resting state functional magnetic resonance imaging and neural network classified autism and control},
  author={Tetsuya Iidaka},
  journal={Cortex},
  year={2015},
  volume={63},
  pages={55-67}
}
Although the neurodevelopmental and genetic underpinnings of autism spectrum disorder (ASD) have been investigated, the etiology of the disorder has remained elusive, and clinical diagnosis continues to rely on symptom-based criteria. In this study, to classify both control subjects and a large sample of patients with ASD, we used resting state functional magnetic resonance imaging (rs-fMRI) and a neural network. Imaging data from 312 subjects with ASD and 328 subjects with typical development… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 55 CITATIONS, ESTIMATED 89% COVERAGE

An enhanced effect-size thresholding method for the diagnosis of Autism Spectrum Disorder using resting state functional MRI

  • 2016 Second International Conference on Cognitive Computing and Information Processing (CCIP)
  • 2016
VIEW 10 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Using regional homogeneity from functional MRI for diagnosis of ASD among males

  • 2015 International Joint Conference on Neural Networks (IJCNN)
  • 2015
VIEW 5 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2015
2019

CITATION STATISTICS

  • 7 Highly Influenced Citations

  • Averaged 14 Citations per year from 2017 through 2019

  • 36% Increase in citations per year in 2019 over 2018