The recent years have witnessed a rapid increase in the number of scientific articles in
biomedical domain. These literature are mostly available and readily accessible in …

Abstract Background Natural Language Processing (NLP) applications have developed
over the past years in various fields including its application to clinical free text for named …

As an essential prodecure to improve design quality in the construction industry, automated
rule checking (ARC) requires intelligent rule interpretation from regulatory texts and precise …

Developing high-performance entity normalization algorithms that can alleviate the term
variation problem is of great interest to the biomedical community. Although deep learning …

This paper describes the SemEval-2014, Task 7 on the Analysis of Clinical Text and
presents the evaluation results. It focused on two subtasks:(i) identification (Task A) and (ii) …

Background Most state-of-the-art biomedical entity normalization systems, such as rule-
based systems, merely rely on morphological information of entity mentions, but rarely …

We examine a key task in biomedical text processing, normalization of disorder mentions.
We present a multi-pass sieve approach to this task, which has the advantage of simplicity …

Text mining of scientific libraries and social media has already proven itself as a reliable tool
for drug repurposing and hypothesis generation. The task of mapping a disease mention to …

In this work, we consider the medical concept normalization problem, ie, the problem of
mapping a health-related entity mention in a free-form text to a concept in a controlled …

Biomedical entity linking aims to map biomedical mentions, such as diseases and drugs, to
standard entities in a given knowledge base. The specific challenge in this context is that the …