arXiv:2204.02208

Abstractive summarization of hospitalisation histories with transformer networks

Alexander Yalunin, Dmitriy Umerenkov, Vladimir Kokh

제출 2022-04-05

원문 초록

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.

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