Candidate biomarkers in psychiatric disorders: state of the field
The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can
aid in objectively diagnosing patients and providing individualized treatment …
aid in objectively diagnosing patients and providing individualized treatment …
Towards a biologically annotated brain connectome
The brain is a network of interleaved neural circuits. In modern connectomics, brain
connectivity is typically encoded as a network of nodes and edges, abstracting away the rich …
connectivity is typically encoded as a network of nodes and edges, abstracting away the rich …
Ensemble model for diagnostic classification of Alzheimer's disease based on brain anatomical magnetic resonance imaging
Alzheimer's is one of the fast-growing diseases among people worldwide leading to brain
atrophy. Neuroimaging reveals extensive information about the brain's anatomy and …
atrophy. Neuroimaging reveals extensive information about the brain's anatomy and …
Functional connectome–based predictive modeling in autism
Autism is a heterogeneous neurodevelopmental condition, and functional magnetic
resonance imaging–based studies have helped advance our understanding of its effects on …
resonance imaging–based studies have helped advance our understanding of its effects on …
Disrupted network integration and segregation involving the default mode network in autism spectrum disorder
B Yang, M Wang, W Zhou, X Wang, S Chen… - Journal of Affective …, 2023 - Elsevier
Abstract Changes in the brain's default mode network (DMN) in the resting state are closely
related to autism spectrum disorder (ASD). Module segmentation can effectively elucidate …
related to autism spectrum disorder (ASD). Module segmentation can effectively elucidate …
Brain functional activity-based classification of autism spectrum disorder using an attention-based graph neural network combined with gene expression
Autism spectrum disorder (ASD) is a complex brain neurodevelopmental disorder related to
brain activity and genetics. Most of the ASD diagnostic models perform feature selection at …
brain activity and genetics. Most of the ASD diagnostic models perform feature selection at …
Meta-connectomic analysis maps consistent, reproducible, and transcriptionally relevant functional connectome hubs in the human brain
Human brain connectomes include sets of densely connected hub regions. However, the
consistency and reproducibility of functional connectome hubs have not been established to …
consistency and reproducibility of functional connectome hubs have not been established to …
Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model
Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic
and brain involvement. Despite magnetic resonance imaging advances, autism spectrum …
and brain involvement. Despite magnetic resonance imaging advances, autism spectrum …
A study of genetic heterogeneity in autism spectrum disorders based on plasma proteomic and metabolomic analysis: multiomics study of autism heterogeneity
X Tang, C Feng, Y Zhao, H Zhang, Y Gao, X Cao… - MedComm, 2023 - Wiley Online Library
Genetic heterogeneity poses a challenge to research and clinical translation of autism
spectrum disorder (ASD). In this study, we conducted a plasma proteomic and metabolomic …
spectrum disorder (ASD). In this study, we conducted a plasma proteomic and metabolomic …
Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders
S Saponaro, F Lizzi, G Serra, F Mainas, P Oliva… - Brain Informatics, 2024 - Springer
Background: The integration of the information encoded in multiparametric MRI images can
enhance the performance of machine-learning classifiers. In this study, we investigate …
enhance the performance of machine-learning classifiers. In this study, we investigate …