ACL 2021short7 citations

Attentive Multiview Text Representation for Differential Diagnosis

Hadi Amiri, Mitra Mohtarami, Isaac Kohane

Abstract

We present a text representation approach that can combine different views (representations) of the same input through effective data fusion and attention strategies for ranking purposes. We apply our model to the problem of differential diagnosis, which aims to find the most probable diseases that match with clinical descriptions of patients, using data from the Undiagnosed Diseases Network. Our model outperforms several ranking approaches (including a commercially-supported system) by effectively prioritizing and combining representations obtained from traditional and recent text representation techniques. We elaborate on several aspects of our model and shed light on its improved performance.

BibTeX
@inproceedings{amiri-etal-2021-attentive,
    title = "Attentive Multiview Text Representation for Differential Diagnosis",
    author = "Amiri, Hadi  and
      Mohtarami, Mitra  and
      Kohane, Isaac",
    editor = "Zong, Chengqing  and
      Xia, Fei  and
      Li, Wenjie  and
      Navigli, Roberto",
    booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.acl-short.128/",
    doi = "10.18653/v1/2021.acl-short.128",
    pages = "1012--1019"
}
Attentive Multiview Text Representation for Differential Diagnosis · ACL 2021