Identification of autism spectrum disorder using deep learning and the ABIDE dataset

• Published in: NeuroImage clinical Vol. 17; pp. 16 - 23
• Main Authors: Heinsfeld, Anibal Sólon, Franco, Alexandre Rosa, Craddock, R. Cameron, Buchweitz, Augusto, Meneguzzi, Felipe
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.01.2018; Elsevier
• Subjects: ABIDE; Adolescent; Adult; Autism; Autism Spectrum Disorder - diagnostic imaging; Brain - diagnostic imaging; Brain Mapping; Case-Control Studies; Child; Datasets as Topic; Deep learning; Female; fMRI; Functional Neuroimaging; Humans; Image Processing, Computer-Assisted; Machine Learning - classification; Male; Neural Networks, Computer; Neural Pathways - diagnostic imaging; Radiology; Regular; Rest; Resting state; Young Adult; Deep learning; Autism; fMRI; ABIDE; Resting state

The goal of the present study was to apply deep learning algorithms to identify autism spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the patients brain activation patterns. We investigated ASD patients brain imaging data from a world-wide multi-site database know...