Chronic Pelvic Inflammatory Disease (CPID) poses significant challenges to women's health, necessitating advanced management strategies. This paper provides a comprehensive review of artificial intelligence (AI)-based health management techniques for PID, focusing on their potential to enhance diagnosis, treatment personalization, and long-term monitoring. By synthesizing Bayesian probabilistic frameworks with ensemble Machine Learning architectures, we systematically evaluate AI-driven solutions for PID pathophysiology analysis, therapeutic efficacy prediction, and patient-specific intervention planning. These approaches collectively enhance diagnostic precision while addressing key challen... More >

The integration of graph neural networks (GNNs) with brain functional network analysis is an emerging field that combines neuroscience and machine learning to enhance our understanding of complex brain dynamics. We first briefly introduce the fundamentals of brain functional networks, followed by an overview of Graph Neural Network principles and architectures. The review then focuses on the applications of these networks and address current challenges in the field, such as the need for interpretable models and effective integration of multi-modal neuroimaging data. We also highlight the potential of GNNs in clinical areas such as perimenopausal depression research, demonstrating the broad a... More >