Background The large volume of medical literature makes it difficult for healthcare
professionals to keep abreast of the latest studies that support Evidence-Based Medicine …

Introduction Clinical data warehouses are often oriented toward integration and exploration
of coded data. However narrative reports are of crucial importance for translational research …

Abstract Natural Language Processing (NLP) applications on real-life textual content require
a suitable fit for purpose corpora, which can accommodate the ambiguity of the domain …

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 …

Objectives: Owing to the rapid progress of natural language processing (NLP), the role of
NLP in the medical field has radically gained considerable attention from both NLP and …

We present CARDIO: DE, the first freely available and distributable large German clinical
corpus from the cardiovascular domain. CARDIO: DE encompasses 500 clinical routine …

Here we describe a new clinical corpus rich in nested entities and a series of neural models
to identify them. The corpus comprises de-identified referrals from the waiting list in Chilean …

Objective We aimed to enhance the performance of a supervised model for clinical named-
entity recognition (NER) using medical terminologies. In order to evaluate our system in …

Unstructured data in electronic health records, represented by clinical texts, are a vast
source of healthcare information because they describe a patient's journey, including clinical …

In sensitive domains, the sharing of corpora is restricted due to confidentiality, copyrights, or
trade secrets. Automatic text generation can help alleviate these issues by producing …