Co-classification network analysis reveals nodal dysfunction and dimension-specific alterations in obstructive sleep apnea-hypopnea syndrome

OSAHS induced widespread nodal dysfunction in brain networks, with distinct changes driven by hypoxemia and apnea frequency. Co-classification network analysis outperforms traditional methods in detecting network abnormalities, and machine learning models based on nodal parameters show high diagnostic accuracy, suggesting potential for OSAHS screening.