CU-UD: text-mining drug and chemical-protein interactions with ensembles of BERT-based models

Autor:	Karabulut, Mehmet Efruz, Vijay-Shanker, K., Peng, Yifan
Rok vydání:	2021
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	Identifying the relations between chemicals and proteins is an important text mining task. BioCreative VII track 1 DrugProt task aims to promote the development and evaluation of systems that can automatically detect relations between chemical compounds/drugs and genes/proteins in PubMed abstracts. In this paper, we describe our submission, which is an ensemble system, including multiple BERT-based language models. We combine the outputs of individual models using majority voting and multilayer perceptron. Our system obtained 0.7708 in precision and 0.7770 in recall, for an F1 score of 0.7739, demonstrating the effectiveness of using ensembles of BERT-based language models for automatically detecting relations between chemicals and proteins. Our code is available at https://github.com/bionlplab/drugprot_bcvii. Comment: Proceedings of the BioCreative VII Challenge Evaluation Workshop
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2112.03004 Zobrazit plný text záznamu View this record from Arxiv