TL;DR
It is demonstrated that the accuracy of diagnosing autism can be improved by investigating the relationships between several behavioural traits using deep learning approach, and the graph-based machine learning models applied to behavioural reaction time features can provide clinically interpretable ASD classification.
The need to develop large, well‐balanced datasets, the application of explainable AI techniques, standardization and regulatory guidelines for facilitating the clinical translation of ASD detection systems are suggested.
The proposed AFSTGCN‐ALA model is evaluated using performance criteria such as compute time, F1‐score, accuracy and precision, and demonstrates the effectiveness and dependability of AFSTGCN‐ALA for early ASD identification.
A novel approach for distinguishing individuals with Autism Spectrum Disorder (ASD) using Intuitionistic Fuzzy Set (IFS) theory and Multi-Scale Enhanced Graph Convolutional Networks (MSE-GCNs), which represents a substantial improvement over existing models for ASD and potentially for other neurological disorders.
This work proposes a cross-attention-guided subject-adaptive graph network (CAS-GNN) model that integrates structural MRI and resting-state functional connectivity data, effectively fusing complementary multimodal information and provides a promising tool for interpretable and robust ASD diagnosis, accelerating biomark...
A benchmarking study on multiple GNNs on a Protein-Protein Interaction (PPI) network for Kidney Renal Clear Cell Carcinoma and Breast cancer subtype prediction, performing an in-depth investigation of architectures, incorporating skip connections and various data modalities.
Study of the efficacy of GNN layers in a slew of regression contexts from rank ordering, error minimization and insight extraction shows that deep convolutional GNNs, particularly GEN, are more effective at these tasks than attention-based GNNs, while other classical, theoretically-inspired GNNs remain competitive and...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
