Hierarchical Neural Networks for Sequential Sentence Classification in Medical Scientific Abstracts

EMNLP 2018  ·  Di Jin, Peter Szolovits ·

Prevalent models based on artificial neural network (ANN) for sentence classification often classify sentences in isolation without considering the context in which sentences appear. This hampers the traditional sentence classification approaches to the problem of sequential sentence classification, where structured prediction is needed for better overall classification performance. In this work, we present a hierarchical sequential labeling network to make use of the contextual information within surrounding sentences to help classify the current sentence. Our model outperforms the state-of-the-art results by 2%-3% on two benchmarking datasets for sequential sentence classification in medical scientific abstracts.

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Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Sentence Classification PubMed 20k RCT Hierarchical Neural Networks F1 92.60 # 1


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