Recent advances in biomedical literature mining

The recent years have witnessed a rapid increase in the number of scientific articles in biomedical domain. These literature are mostly available and readily accessible in electronic format. The domain knowledge hidden in them is critical for biomedical research and applications, which makes biomedical literature mining (BLM) techniques highly demanding. Numerous efforts have been made on this topic from both biomedical informatics (BMI) and computer science (CS) communities. The BMI community focuses more on the concrete application problems and thus prefer more interpretable and descriptive methods, while the CS community chases more on superior performance and generalization ability, thus more sophisticated and universal models are developed. The goal of this paper is to provide a review of the recent advances in BLM from both communities and inspire new research directions.

Automated summary

In recent years, there has been a rapid increase in scientific articles in the biomedical domain, leading to a high demand for biomedical literature mining techniques. Efforts from both the BMI and CS communities have focused on developing more interpretable and descriptive methods in the BMI community, while the CS community has been more focused on superior performance and generalization ability, leading to the development of more sophisticated and universal models. A review of recent advances in BLM from both communities aims to inspire new research directions.