Machine Learning-based Diagnosis of Autism Spectrum Disorder Using Brain Imaging

Abstract

In spite of research over the past decades, robust, replicable, and clinically translatable markers to objectively diagnose psychiatric disorders are yet to be ascertained. Several factors such as biological heterogeneity (partly due to the complex genetic basis that is further compounded by environmental interactions), the potential mismatch between contemporary diagnostic criteria / clinical symptom scores and findings that emanate from cutting-edge neuroscience observations, and similar others have made the identification of biomarkers a daunting challenge. This challenge becomes much harder to solve in the context of disorders of childhood onset such as, autism spectrum disorders (ASD) especially because of the additional complexity of examining the developing brain.