Medication Mining

Medication mining focuses on automatically extracting medication information and related temporal data from diverse text sources, such as electronic health records and social media, to improve healthcare. Current research emphasizes the application of deep learning models, including recurrent neural networks (like BiLSTM-CRF) and transformer-based architectures (like BERT and its variants), often enhanced by techniques like data augmentation, to achieve accurate and robust medication entity recognition and relation extraction. These advancements hold significant promise for enhancing clinical decision support, improving patient safety through anomaly detection in prescriptions, and facilitating public health surveillance by analyzing social media data.