NER systems in epidemiology are often built using machine learning and deep learning techniques. These systems are trained on annotated corpora that include epidemiological texts. Common methods include:
Rule-Based Approaches: Utilize predefined rules and patterns to identify entities. Statistical Models: Employ algorithms like Hidden Markov Models (HMM) and Conditional Random Fields (CRF). Neural Networks: Use architectures such as Recurrent Neural Networks (RNN) and Transformer models like BERT.
