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Abstractive summarization of hospitalisation histories with transformer networks

2022-04-05 13:38:39
Alexander Yalunin, Dmitriy Umerenkov, Vladimir Kokh
arXiv_CL
       
Abstract

In this paper we present a novel approach to abstractive summarization of patient hospitalisation histories. We applied an encoder-decoder framework with Longformer neural network as an encoder and BERT as a decoder. Our experiments show improved quality on some summarization tasks compared with pointer-generator networks. We also conducted a study with experienced physicians evaluating the results of our model in comparison with PGN baseline and human-generated abstracts, which showed the effectiveness of our model.

Abstract (translated)

URL

https://arxiv.org/abs/2204.02208

PDF

https://arxiv.org/pdf/2204.02208.pdf

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