Model | Accuracy | Precision | Recall | F1-score |
---|
BERT [20]a | *0.849 **(0.003) | 0.817 (0.010) | 0.822 (0.019) | 0.818 (0.011) |
BioBERT [31]b | 0.861 (0.008) | 0.835 (0.017) | 0.846 (0.015) | 0.839 (0.011) |
PubMedBERT[34]c | 0.865 (0.014) | 0.833 (0.020) | 0.849 (0.009) | 0.839 (0.015) |
RoBERTa [35]d | 0.862 (0.009) | 0.835 (0.018) | 0.837 (0.009) | 0.835 (0.010) |
SciBERT [32]e | 0.862 (0.010) | 0.836 (0.017) | 0.843 (0.013) | 0.838 (0.013) |
- The best scores are in bold
- *Mean
- **Standard deviation
- aBert-base-uncased, Accessed July 20, 2022, Available from: https://huggingface.co/bert-base-uncased
- bBiobert-base-cased-v1.2, Accessed July 20, 2022, Available from: https://huggingface.co/dmis-lab/biobert-base-cased-v1.2
- cBiomedNLP-PubMedBERT-base-uncased-abstract-fulltext, Accessed July 20, 2022, Available from: https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
- dRoberta-base, Accessed July 20, 2022, Available from: https://huggingface.co/roberta-base
- eScibert_scivocab_uncased, Accessed July 20, 2022, Available from: https://huggingface.co/allenai/scibert_scivocab_uncased