Anxiety Disorder

Anxiety disorders are a significant public health concern, and research focuses on developing accurate and efficient diagnostic tools. Current efforts utilize machine learning, employing diverse architectures like support vector machines, random forests, deep learning models (including convolutional and recurrent neural networks), and transformer models, to analyze various data sources including physiological signals (EEG, ECG, EDA), linguistic features from speech and text, and even environmental imagery. These advancements aim to improve early detection and personalized treatment, potentially leading to more effective and accessible mental healthcare interventions.