A comprehensive review of AI-powered wearable biosensors emphasizing how machine learning and edge AI enable real-time health monitoring and personalized care, with insights on digital twins, LLMs, and challenges in privacy, scalability, and clinical integration.
We developed GlucoLens, that takes sensor-driven inputs and uses advanced data processing, large language models, and explainable machine learning models to predict postprandial AUC and hyperglycemia from diet, physical activity, and recent glucose patterns.