Fig. 1

Implementation workflow of EpiPipeline4RD. A Steps applied to prepare ES data for deep learning model training. EMBL-EBI refers to the EBI API for gathering abstracts. ES_Predict is a Long Short-Term Memory Recurrent Neural Network for ES prediction. B Methods applied for the epidemiology corpus generation. Distant supervision draws upon the NGKG from Neo4J and Wikipedia. Noisy supervision draws upon a spaCy NER model. Prescriptive supervision is dependent upon rules described in the Additional file 2. C Transformer model architecture. Positional embeddings are added to the WordPiece embeddings. “Add” refers to the addition of the sub-layer output to its input (residual connection). “Norm” refers to sub-layer normalization after employing a residual connection [55]. D EpiPipeline4RD implementation. Output of the EI extraction via the User Interface