Word embeddings have been widely used in Natural Language Processing (NLP) tasks.
Although these representations can capture the semantic information of words, they cannot …

Background Natural language processing (NLP) enables the extraction of information
embedded within unstructured texts, such as clinical case reports and trial eligibility criteria …

Annotated corpora are essential to reliable natural language processing. While they are
expensive to create, they are essential for building and evaluating systems. This study …

Background Medical lexicons enable the natural language processing (NLP) of health texts.
Lexicons gather terms and concepts from thesauri and ontologies, and linguistic data for part …

As the field of Nested Named Entity Recognition (NNER) advances, it is marked by a
growing complexity due to the increasing number of multi-label entity instances. How to …

The extraction and classification of important information from Spanish Electronic Clinical
Narratives (ECNs) can be challenging due to the complexity of the clinical text and the …

Using language models created from large data sources has improved the performance of
several deep learning-based architectures, obtaining state-of-the-art results in several NLP …

Despite the high creation cost, annotated corpora are indispensable for robust natural
language processing systems. In the clinical field, in addition to annotating medical entities …

Abstract We introduce the Bias Network Approach (BNA) as a sociotechnical method for AI
developers to identify, map, and relate biases across the AI development process. This …

Las listas de espera no cubiertas por el Plan de Garantías Explícitas en Salud para nueva
consulta de especialidad en Chile se han visto incrementadas por los efectos de la …