Discrete and Continuous Models and Applied Computational ScienceDiscrete and Continuous Models and Applied Computational ScienceDiscrete and Continuous Models and Applied Computational Science2658-46702658-7149Peoples' Friendship University of Russia named after Patrice Lumumba (RUDN University)3446310.22363/2658-4670-2023-31-1-64-74VNWSXIArticlesСтатьиResearch ArticleMethods of extracting biomedical information from patents and scientific publications (on the example of chemical compounds)Методы извлечения биомедицинских текстов из патентов и научных публикаций (на примере химических соединений)https://orcid.org/0000-0002-1640-1357KolpakovNikolay A.КолпаковН. А.

Master’s degree student of Phystech School of Applied Mathematics and Informatics

kolpakov.na@phystech.eduhttps://orcid.org/0000-0003-0039-943XMolodchenkovAlexey I.МолодченковА. И.

Candidate of Technical Sciences, Federal Research Center “Computer Science and Control” of RAS employee, employee of the Peoples’ Friendship University of Russia

aim@tesyan.ruhttps://orcid.org/0000-0003-4391-1958LukinAnton V.ЛукинА. В.

Federal Research Center “Computer Science and Control” of RAS employee, employee of the Peoples’ Friendship University of Russia

antonvlukin@gmail.comMoscow Institute of Physics and Technology (MIPT)Московский физико-технический институтFederal research center “Computer science and control” of RASФедеральный исследовательский центр «Информатика и управление» РАНPeoples’ Friendship University of Russia (RUDN University)Российский университет дружбы народов30032023311VOL 31, NO1 (2023)ТОМ 31, №1 (2023)647420042023Copyright ©; 2023, Kolpakov N.A., Molodchenkov A.I., Lukin A.V.Copyright ©; 2023, Колпаков Н.А., Молодченков А.И., Лукин А.В.2023Kolpakov N.A., Molodchenkov A.I., Lukin A.V.Колпаков Н.А., Молодченков А.И., Лукин А.В.https://creativecommons.org/licenses/by-nc/4.0https://journals.rudn.ru/miph/article/view/34463

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.

В данной статье предложен алгоритм для решения задачи извлечения информации из биомедицинских патентов и научных публикаций. Представленный алгоритм основан на методах машинного обучения. Авторами были проведены эксперименты на патентах из базы USPTO. Эксперименты показали, что лучшее качество извлечения продемонстрировала модель, построенная на основе BioBERT.

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