Neuroimaging-based individualized prediction of cognition and behavior for mental disorders and health: methods and promises
The neuroimaging community has witnessed a paradigm shift in biomarker discovery from
using traditional univariate brain mapping approaches to multivariate predictive models …
using traditional univariate brain mapping approaches to multivariate predictive models …
Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging
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 …
diagnostic period encountered in the early years of life. If diagnosed early, the negative …
Atypical functional connectome hierarchy in autism
One paradox of autism is the co-occurrence of deficits in sensory and higher-order socio-
cognitive processing. Here, we examined whether these phenotypical patterns may relate to …
cognitive processing. Here, we examined whether these phenotypical patterns may relate to …
Diagnostic of autism spectrum disorder based on structural brain MRI images using, grid search optimization, and convolutional neural networks
In this study, an automatic autism diagnostic model based on sMRI is proposed. This
proposed model consists of two basic stages. The first stage is the preprocessing stage …
proposed model consists of two basic stages. The first stage is the preprocessing stage …
Applications of supervised machine learning in autism spectrum disorder research: a review
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 …
as other fields; however, advancements in easy, affordable data collection and analysis may …
Transfer learning in magnetic resonance brain imaging: A systematic review
(1) Background: Transfer learning refers to machine learning techniques that focus on
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
Identifying autism spectrum disorder with multi-site fMRI via low-rank domain adaptation
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is characterized by a
wide range of symptoms. Identifying biomarkers for accurate diagnosis is crucial for early …
wide range of symptoms. Identifying biomarkers for accurate diagnosis is crucial for early …
[HTML][HTML] Evaluation of machine learning algorithms for health and wellness applications: A tutorial
J Tohka, M Van Gils - Computers in Biology and Medicine, 2021 - Elsevier
Research on decision support applications in healthcare, such as those related to diagnosis,
prediction, treatment planning, etc., has seen strongly growing interest in recent years. This …
prediction, treatment planning, etc., has seen strongly growing interest in recent years. This …
[HTML][HTML] Dissecting the heterogeneous cortical anatomy of autism spectrum disorder using normative models
Background The neuroanatomical basis of autism spectrum disorder (ASD) has remained
elusive, mostly owing to high biological and clinical heterogeneity among diagnosed …
elusive, mostly owing to high biological and clinical heterogeneity among diagnosed …
A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective
Abstract Autism Spectrum Disorder (ASD) affects approximately 1% of the population and
leads to impairments in social interaction, communication and restricted, repetitive …
leads to impairments in social interaction, communication and restricted, repetitive …