Fig. 2.

An overview of BERT-based multi-classification models for biomedical literature using an example of classifying two labels (Labels 1 and 2). (A): Binary BERT: train a BERT model for each label; (B) Linear BERT: train a shared BERT model and output all the label probabilities at once; (C): LitMC-BERT (our proposed approach): train a shared BERT model, capture label-based features (Label Module) and models pair relations (Label Pair Module), and also predict both labels and their co-occurrences via co-training.