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3 months ago

Integration of Deep Learning and Traditional Machine Learning for Knowledge Extraction from Biomedical Literature

{Wanli Liu Jihang Mao}

Integration of Deep Learning and Traditional Machine Learning for Knowledge Extraction from Biomedical Literature

Abstract

In this paper, we present our participation in the Bacteria Biotope (BB) task at BioNLP-OST 2019. Our system utilizes fine-tuned language representation models and machine learning approaches based on word embedding and lexical features for entities recognition, normalization and relation extraction. It achieves the state-of-the-art performance and is among the top two systems in five of all six subtasks.

Benchmarks

BenchmarkMethodologyMetrics
medical-concept-normalization-on-bb-norm-1BLAIR GMU
accuracy: 0.211
wang: 0.615
medical-concept-normalization-on-bb-norm-2BLAIR GMU
accuracy: 0.313
wang: 0.646

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Integration of Deep Learning and Traditional Machine Learning for Knowledge Extraction from Biomedical Literature | Papers | HyperAI