Relevant Pain Information

Research on relevant pain information focuses on automatically detecting and interpreting pain, primarily through analysis of facial expressions, physiological signals (like ECG), and language. Current approaches leverage deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), vision transformers, and knowledge graph embeddings, to analyze diverse data sources and predict pain intensity or type. This work aims to improve pain assessment, particularly in challenging scenarios like nonverbal patients or animals, leading to more objective and efficient healthcare and potentially informing the development of new pain treatments.