Frontiers | Autism Spectrum Disorder Studies Using fMRI Data and Machine Learning: A Review
Extended Invariant Information Clustering is Effective for Leave-One-Site-Out Cross-Validation in Resting State Functional Conne
Attentional Connectivity-based Prediction of Autism Using Heterogeneous rs-fMRI Data from CC200 Atlas
MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites | PLOS ONE
GitHub - czarrar/abide: Scripts related to preprocessing the ABIDE dataset and generating relevant derivatives
Developing predictive imaging biomarkers using whole-brain classifiers: Application to the ABIDE I dataset
Big Data for Discovery Science / Big Data to Knowledge
Examples of MRI artifacts in T1 volumes present in the ABIDE dataset. a... | Download Scientific Diagram
Generalizability and reproducibility of functional connectivity in autism | Molecular Autism | Full Text
Preprocessed Connectomes Project
IRJET- Analysis of Autism Spectrum Disorder using Deep Learning and the Abide Dataset
Autism predictions from the ABIDE dataset. See Fig. 10 and 11 for legends. | Download Scientific Diagram
IRJET- Analysis of Autism Spectrum Disorder using Deep Learning and the Abide Dataset
Twitter \ Raphaël Béné على تويتر: "Involvement of the habenula in the pathophysiology of autism spectrum disorder. https://t.co/6uojRnI3fR Habenula volumes were estimated using scans from the Autism Brain Imaging Data Exchange (ABIDE).
Using Functional or Structural Magnetic Resonance Images and Personal Characteristic Data to Identify ADHD and Autism | PLOS ONE
Enhancing studies of the connectome in autism using the autism brain imaging data exchange II | Scientific Data
Study seeks autism biomarkers in brain-imaging database | Spectrum | Autism Research News
A hitchhiker's guide to working with large, open-source neuroimaging datasets | Nature Human Behaviour
Improving multi-site autism classification based on site-dependence minimisation and second-order functional connectivity | bioRxiv
Supplemental Information
Identification of autism spectrum disorder using deep learning and the ABIDE dataset - ScienceDirect