Named Entity Recognition (NER) refers to the task of locating relevant information within text
sequences. Within the medical domain, it can benefit applications such as de-identifying …

The task of Named Entity Recognition (NER) is central for leveraging the content of clinical
texts in observational studies. Indeed, texts contain a large part of the information available …

Medical data can be used to perform analyses and research in the medical domain.
However, large percentages of the data remain unstructured and thus unused after they are …

One of the central tasks of medical text analysis is to extract and structure meaningful
information from plain-text clinical documents. Named Entity Recognition (NER) is a sub …

Biomedical named entity recognition (NER) is a critial task that aims to identify structured
information in clinical text, which is often replete with complex, technical terms and a high …

Abstract Named Entity Recognition (NER) task aims to identify named entities from
unstructured text and classify them into corresponding entity types. Existing pretraining …

To be able to share the valuable information in electronic patient records (EPR) they first
need to be de-identified in order to protect the privacy of their subjects. Named entity …

This report presents a project that aims to develop Named Entity Recognition (NER) models
for two datasets in the medical domain: emergency hotline data and N2C2 clinical notes …

Named entity recognition (NER) and normalization are crucial tasks for information
extraction in the medical field. They have been tackled through different approaches from …

Abstract Named Entity Recognition (NER) tools have been in development for years, yet few
have been aimed at medical documents. The increasing needs for analyzing medical data …