Natural hazard named entity recognition is a technique used to recognize natural hazard
entities from a large number of texts. The method of natural hazard named entity recognition …

Recent advances in NLP techniques, the use of large language models and Transformers
are showing promising results for processing clinical content. The development of tools for …

Clinical named entity recognition plays an important role in the field of clinical research
based on clinical information mining. The objective of clinical named entity recognition is to …

Large-scale sensitive information leakage incidents are frequently reported in recent years.
Once sensitive information is leaked, it may lead to serious effects. In this context, sensitive …

The large availability of clinical natural language documents, such as clinical narratives or
diagnoses, requires the definition of smart automatic systems for their processing and …

Named entity recognition aims to identify and mark entities with specific meanings in text. It
is a key technology to further extract entity relationships and mine other potential information …

The unprecedented growth in the use of social media platforms, where opinions and
decisions are made and updated within seconds. Hence, Twitter is becoming a huge …

Background Information related to patient medication is crucial for health care; however, up
to 80% of the information resides solely in unstructured text. Manual extraction is difficult and …

Background In recent years, health data collected during the clinical care process have
been often repurposed for secondary use through clinical data warehouses (CDWs), which …

Introduction Concept normalization is the task of linking terms from textual medical
documents to their concept in terminologies such as the UMLS®. Traditional approaches to …