no code implementations • WS 2018 • Manirupa Das, Eric Fosler-Lussier, Simon Lin, Soheil Moosavinasab, David Chen, Steve Rust, Yungui Huang, Rajiv Ramnath
In this work, we develop a novel, completely unsupervised, neural language model-based document ranking approach to semantic tagging of documents, using the document to be tagged as a query into the GLM to retrieve candidate phrases from top-ranked related documents, thus associating every document with novel related concepts extracted from the text.
1 code implementation • 21 Jun 2019 • Zhen Wang, Xiang Yue, Soheil Moosavinasab, Yungui Huang, Simon Lin, Huan Sun
To solve the problem, we propose a new framework SurfCon that leverages two important types of information in the privacy-aware clinical data, i. e., the surface form information, and the global context information for synonym discovery.
no code implementations • 13 Sep 2019 • Xianlong Zeng, Soheil Moosavinasab, En-Ju D Lin, Simon Lin, Razvan Bunescu, Chang Liu
Efficient representation of patients is very important in the healthcare domain and can help with many tasks such as medical risk prediction.
no code implementations • 11 Nov 2019 • Manirupa Das, Juanxi Li, Eric Fosler-Lussier, Simon Lin, Soheil Moosavinasab, Steve Rust, Yungui Huang, Rajiv Ramnath
Our approach to generate document encodings employing our sequence-to-set models for inference of semantic tags, gives to the best of our knowledge, the state-of-the-art for both, the unsupervised query expansion task for the TREC CDS 2016 challenge dataset when evaluated on an Okapi BM25--based document retrieval system; and also over the MLTM baseline (Soleimani et al, 2016), for both supervised and semi-supervised multi-label prediction tasks on the del. icio. us and Ohsumed datasets.
1 code implementation • ACL 2020 • Zhen Wang, Jennifer Lee, Simon Lin, Huan Sun
Nowadays, the interpretability of machine learning models is becoming increasingly important, especially in the medical domain.
no code implementations • WS 2020 • Manirupa Das, Juanxi Li, Eric Fosler-Lussier, Simon Lin, Steve Rust, Yungui Huang, Rajiv Ramnath
Novel contexts, comprising a set of terms referring to one or more concepts, may often arise in complex querying scenarios such as in evidence-based medicine (EBM) involving biomedical literature.
1 code implementation • EMNLP 2021 • Xinliang Frederick Zhang, Heming Sun, Xiang Yue, Simon Lin, Huan Sun
For evaluation, we introduce Query Bank and Relevance Set, where the former contains 1, 236 human-paraphrased queries while the latter contains ~32 human-annotated FAQ items for each query.
2 code implementations • 30 Oct 2020 • Xiang Yue, Xinliang Frederick Zhang, Ziyu Yao, Simon Lin, Huan Sun
Clinical question answering (QA) aims to automatically answer questions from medical professionals based on clinical texts.
no code implementations • 23 Jun 2021 • Xianlong Zeng, Simon Lin, Chang Liu
The claims data, containing medical codes, services information, and incurred expenditure, can be a good resource for estimating an individual's health condition and medical risk level.
no code implementations • 24 Jun 2021 • Xianlong Zeng, Simon Lin, Chang Liu
In addition, our framework showed a great generalizability potential to transfer learned knowledge from one institution to another, paving the way for future healthcare model pre-training across institutions.