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

WS 2019  ·  Jihang Mao, Wanli Liu ·

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.

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Task Dataset Model Metric Name Metric Value Global Rank Benchmark
Medical Concept Normalization BB-norm-habitat BLAIR GMU wang 0.615 # 4
accuracy 0.211 # 4
Medical Concept Normalization BB-norm-phenotype BLAIR GMU wang 0.646 # 3
accuracy 0.313 # 4

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