Significant growth in Electronic Health Records (EHR) over the last decade has provided an
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …

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 …

In recent years pre-trained language models (PLM) such as BERT have proven to be very
effective in diverse NLP tasks such as Information Extraction, Sentiment Analysis and …

In recent years extracting relevant information from biomedical and clinical texts such as
research articles, discharge summaries, or electronic health records have been a subject of …

Geological reports aid in understanding exploration by providing valuable information on
rock formation, evolution and the geological environment in which deposits formed …

As the significant subtask of information extraction, relation extraction (RE) aims to identify
and classify semantic relations between pairs of entities and is widely adopted as the …

Biomedical information extraction (BioIE) is important to many applications, including clinical
decision support, integrative biology, and pharmacovigilance, and therefore it has been an …

Reliably detecting relevant relations between entities in unstructured text is a valuable
resource for knowledge extraction, which is why it has awaken significant interest in the field …

Background The limited availability of clinical texts for Natural Language Processing
purposes is hindering the progress of the field. This article investigates the use of synthetic …

Over 50 million scholarly articles have been published: they constitute a unique repository of
knowledge. In particular, one may infer from them relations between scientific concepts …