Reproducible Neuroimaging Features for Diagnosis of Autism Spectrum Disorder with Machine Learning

Abstract excerpt

Autism spectrum disorder (ASD) is the fourth most common neurodevelopmental disorder, with a prevalence of 1 in 160 children. Accurate diagnosis relies on experts, but such individuals are scarce. This has led to increasing interest in the development of machine learning (ML) models that can integrate neuroimaging features from functional and structural MRI (fMRI and sMRI) to measure alterations manifest in ASD. W...

Topics

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• Autism Spectrum Disorder
• Child
• Cluster Analysis
• Clustering Algorithms
• Gene Expression Profiling
• Machine Learning
• Phenotype
• Transcriptome

Identifiers and source

Literature Corpus work

e71207c9-4491-5fee-8502-fa13e10654d5

DOI

10.21203/rs.3.rs-1024223/v1