Advancing ASD detection: novel approach integrating attention graph neural networks and crossover boosted meerkat optimization

• Published in: International journal of machine learning and cybernetics Vol. 15; no. 8; pp. 3279 - 3297
• Main Authors: Goel, Lipika, Gupta, Sonam, Gupta, Avdhesh, Rajan, Siddhi Nath, Gupta, Vishan Kumar, Singh, Arjun, Gupta, Pradeep
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2024; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Artificial Intelligence; Autism; Behavior; Brain research; Classification; Cognition & reasoning; Communication; Complex Systems; Computational Intelligence; Computing time; Control; Crossovers; Datasets; Engineering; Feature extraction; Graph neural networks; Image quality; Literature reviews; Machine learning; Magnetic resonance imaging; Mechatronics; Medical imaging; Neural networks; Neurodevelopmental disorders; Optimization; Original Article; Pattern Recognition; Performance evaluation; Quality of life; Robotics; Soft tissues; Support vector machines; Systems Biology; Image quality; Attention mechanism; Magnetic resonance imaging; Structural magnetic resonance imaging; Graph neural network; Convergence and classification loss; Crossover operation; Meerkat optimization; Autism spectrum disorder; Voxel morphometry
• ISSN: 1868-8071; 1868-808X
• DOI: 10.1007/s13042-023-02092-1

Autism spectrum disorder (ASD) is a neurodevelopmental condition that significantly impacts the lives of many children due to its hidden symptoms. Early detection of ASD is challenging because of its complex and heterogeneous nature. Magnetic resonance imaging (MRI) has emerged as a crucial tool for...