Deep reinforcement learning for fMRI prediction of Autism Spectrum Disorder. (arXiv:2206.11224v1 [q-bio.NC])

Purpose : Because functional MRI (fMRI) data sets are in general small, we
sought a data efficient approach to resting state fMRI classification of autism
spectrum disorder (ASD) versus neurotypical (NT) controls. We hypothesized that
a Deep Reinforcement Learning (DRL) classifier could learn effectively on a
small fMRI training set.

Methods : We trained a Deep Reinforcement Learning (DRL) classifier on 100
graph-label pairs from the Autism Brain Imaging Data Exchange (ABIDE) database.
For comparison, we trained a Supervised Deep …

arxiv autism bio learning prediction reinforcement reinforcement learning