Short Review on srBERT: Automatic Article Classification Model for Systematic Review Using BERT

Abstract

Systematic reviews (SRs) have been recognized as the most rigorous and reliable approach to enable evidence-based medicine. However, the considerable workload required to create SRs prevents reflecting the latest knowledge. This study automated the classification of included articles by adopting the Bidirectional Encoder Representations from Transformers (BERT) algorithm. By pretraining with abstracts of articles and a generated vocabulary fine-tuned with titles of articles, the proposed srBERTmy overcomes the training data insufficiency while improving performance in both classification and relation-extraction tasks. Despite the limitation of model vulnerabilities based on training dataset quality, the results demonstrated the feasibility of automatic article classification using machine-learning (ML) approaches to support SR tasks Keywords: Systematic review, process automation, deep learning, text mining