NER for Medical Entities in Twitter using Sequence to Sequence Neural Networks

Social media sites such as Twitter are attractive sources of information due to their combination of accessibility, timeliness and large data volumes. Identification of medical entities in Twitter can support tasks such public health surveillance. We propose an approach to perform annotation of medical entities using a sequence to sequence neural network. Results show that our approach improves over previous work based on CRF in the annotation of two medical entities types in Twitter.