| Literature DB >> 33551784 |
Taban Eslami1, Fahad Almuqhim2, Joseph S Raiker3, Fahad Saeed2.
Abstract
Here we summarize recent progress in machine learning model for diagnosis of Autism Spectrum Disorder (ASD) and Attention-deficit/Hyperactivity Disorder (ADHD). We outline and describe the machine-learning, especially deep-learning, techniques that are suitable for addressing research questions in this domain, pitfalls of the available methods, as well as future directions for the field. We envision a future where the diagnosis of ASD, ADHD, and other mental disorders is accomplished, and quantified using imaging techniques, such as MRI, and machine-learning models.Entities:
Keywords: Attention Deficit and Hyperactivity Disorder (ADHD) classification; Autism Spectrum Disorder (ASD) classification; deep learning; diagnosis; fMRI; machine learning; sMRI; survey
Year: 2021 PMID: 33551784 PMCID: PMC7855595 DOI: 10.3389/fninf.2020.575999
Source DB: PubMed Journal: Front Neuroinform ISSN: 1662-5196 Impact factor: 4.081