Methods of extracting biomedical information from patents and scientific publications (on the example of chemical compounds)

Abstract

This article proposes an algorithm for solving the problem of extracting information from biomedical patents and scientific publications. The introduced algorithm is based on machine learning methods. Experiments were carried out on patents from the USPTO database. Experiments have shown that the best extraction quality was achieved by a model based on BioBERT.

Keywords

• machine learning
• natural language processing
• named entity recognition
• biomedical texts processing