Healthy Subject

Research on "healthy subjects" focuses on establishing robust baselines for various physiological and behavioral metrics, crucial for developing accurate diagnostic and monitoring tools. Current studies utilize machine learning, particularly deep learning models like convolutional neural networks and variational autoencoders, to analyze data from diverse sources including fMRI, wearable sensors, and even smartphone cameras, aiming to identify patterns indicative of health and disease. This work is significant because it enables the development of AI-driven tools for objective, efficient, and potentially cost-effective assessment of health status and disease severity across various conditions, improving clinical practice and patient care.