论文标题
通过变压器网络对住院历史的抽象摘要
Abstractive summarization of hospitalisation histories with transformer networks
论文作者
论文摘要
在本文中，我们提出了一种新颖的方法，用于对患者住院历史进行抽象性汇总。我们将用长形神经网络用作编码器的编码器框架将编码器框架应用于解码器。与指针生成网络相比，我们的实验显示了一些摘要任务的质量提高。我们还对经验丰富的医生进行了一项研究，该研究与PGN基线和人类生成的摘要相比，评估了我们的模型结果，这显示了我们的模型的有效性。
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.
