Methods of extracting biomedical information from patents and scientific publications (on the example of chemical compounds)
Journal: Discrete and Continuous Models and Applied Computational Science (Vol.31, No. 1)Publication Date: 2023-04-21
Authors : Nikolay Kolpakov; Alexey Molodchenkov; Anton Lukin;
Page : 64-74
Keywords : machine learning; natural language processing; named entity recognition; biomedical texts processing;
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.
Other Latest Articles
- Causality relationship between foreign direct investments and economic improvement for developing economies: Russia case study
- Construction, stochastization and computer study of dynamic population models “two competitors - two migration areas”
- Julia language features for processing statistical data
- Exploring Controversial Issues: Discursive Devices in Duterte’s Speeches
- Similarities of First- and Second- Hand Accounts of Cancer Diagnoses by Two Physicians in the Literature
Last modified: 2023-04-21 05:34:44