Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
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 …
symptoms that appear in early childhood. ASD is also associated with communication …
rs-fMRI and machine learning for ASD diagnosis: a systematic review and meta-analysis
Abstract Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria
through a lengthy and time-consuming process. Much effort is being made to identify brain …
through a lengthy and time-consuming process. Much effort is being made to identify brain …
Artificial intelligence for brain diseases: A systematic review
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 …
analyzing complex medical data and extracting meaningful relationships in datasets, for …
Identifying autism spectrum disorder from resting-state fMRI using deep belief network
With the increasing prevalence of autism spectrum disorder (ASD), it is important to identify
ASD patients for effective treatment and intervention, especially in early childhood …
ASD patients for effective treatment and intervention, especially in early childhood …
Machine learning for autism spectrum disorder diagnosis using structural magnetic resonance imaging: Promising but challenging
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects
approximately 1% of the population and causes significant burdens. ASD's pathogenesis …
approximately 1% of the population and causes significant burdens. ASD's pathogenesis …
A classification framework for Autism Spectrum Disorder detection using sMRI: Optimizer based ensemble of deep convolution neural network with on-the-fly data …
Abstract Autism Spectrum Disorder (ASD) has affected many children's life due to their
hidden symptoms. The late detection of ASD is due to its complex and heterogeneous …
hidden symptoms. The late detection of ASD is due to its complex and heterogeneous …
Using explainable artificial intelligence in the clock drawing test to reveal the cognitive impairment pattern
C Jiménez-Mesa, JE Arco, M Valentí-Soler… - … Journal of Neural …, 2023 - World Scientific
The prevalence of dementia is currently increasing worldwide. This syndrome produces a
deterioration in cognitive function that cannot be reverted. However, an early diagnosis can …
deterioration in cognitive function that cannot be reverted. However, an early diagnosis can …
Brain imaging-based machine learning in autism spectrum disorder: methods and applications
Autism spectrum disorder (ASD) is a neurodevelopmental condition with early childhood
onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is …
onset and high heterogeneity. As the pathogenesis is still elusive, ASD diagnosis is …
Machine learning methods for brain network classification: Application to autism diagnosis using cortical morphological networks
Background Autism spectrum disorder (ASD) affects the brain connectivity at different levels.
Nonetheless, non-invasively distinguishing such effects using magnetic resonance imaging …
Nonetheless, non-invasively distinguishing such effects using magnetic resonance imaging …
Alzheimer's disease prediction via brain structural-functional deep fusing network
Q Zuo, Y Shen, N Zhong, CLP Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Fusing structural-functional images of the brain has shown great potential to analyze the
deterioration of Alzheimer's disease (AD). However, it is a big challenge to effectively fuse …
deterioration of Alzheimer's disease (AD). However, it is a big challenge to effectively fuse …