Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging

HS Nogay, H Adeli - Reviews in the Neurosciences, 2020 - degruyter.com
Autism spectrum disorder (ASD) is a neurodevelopmental incurable disorder with a long
diagnostic period encountered in the early years of life. If diagnosed early, the negative …

Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review

P Moridian, N Ghassemi, M Jafari… - Frontiers in Molecular …, 2022 - frontiersin.org
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …

Artificial intelligence for brain diseases: A systematic review

A Segato, A Marzullo, F Calimeri, E De Momi - APL bioengineering, 2020 - pubs.aip.org
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …

Applications of supervised machine learning in autism spectrum disorder research: a review

KK Hyde, MN Novack, N LaHaye… - Review Journal of …, 2019 - Springer
Autism spectrum disorder (ASD) research has yet to leverage “big data” on the same scale
as other fields; however, advancements in easy, affordable data collection and analysis may …

[HTML][HTML] Classification of children with autism and typical development using eye-tracking data from face-to-face conversations: Machine learning model development …

Z Zhao, H Tang, X Zhang, X Qu, X Hu, J Lu - Journal of Medical Internet …, 2021 - jmir.org
Background Previous studies have shown promising results in identifying individuals with
autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data …

Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry

Z Chen, B Hu, X Liu, B Becker, SB Eickhoff, K Miao… - BMC medicine, 2023 - Springer
Background The development of machine learning models for aiding in the diagnosis of
mental disorder is recognized as a significant breakthrough in the field of psychiatry …

Evaluation of risk of bias in neuroimaging-based artificial intelligence models for psychiatric diagnosis: a systematic review

Z Chen, X Liu, Q Yang, YJ Wang, K Miao… - JAMA network …, 2023 - jamanetwork.com
Importance Neuroimaging-based artificial intelligence (AI) diagnostic models have
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …

Identifying autism with head movement features by implementing machine learning algorithms

Z Zhao, Z Zhu, X Zhang, H Tang, J **ng, X Hu… - Journal of Autism and …, 2022 - Springer
Our study investigated the feasibility of using head movement features to identify individuals
with autism spectrum disorder (ASD). Children with ASD and typical development (TD) were …

Brain imaging-based machine learning in autism spectrum disorder: methods and applications

M Xu, V Calhoun, R Jiang, W Yan, J Sui - Journal of neuroscience methods, 2021 - Elsevier
Autism spectrum disorder (ASD) is a neurodevelopmental condition with early childhood
onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is …

Reproducible neuroimaging features for diagnosis of autism spectrum disorder with machine learning

CJ Mellema, KP Nguyen, A Treacher, A Montillo - Scientific reports, 2022 - nature.com
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 …