Fat Prediction

Fat prediction research focuses on accurately estimating body fat percentage and distribution, crucial for assessing health risks and guiding interventions. Current approaches leverage diverse data sources, including single images analyzed by deep neural networks (like ShapedNet), body surface meshes processed by graph neural networks, and multimodal data integrated via deep learning architectures. These methods aim to improve accuracy and efficiency compared to traditional methods, offering valuable tools for personalized healthcare and obesity management, particularly through improved diet recommendations informed by machine learning models.