Pretrained language models augmented with in-domain corpora show impressive results in
biomedicine and clinical Natural Language Processing (NLP) tasks in English. However …

Pretrained language models elevated with in-domain corpora show impressive results in
biomedicine and clinical NLP tasks in English. However, there is minimal work in low …

In recent years, major advancements in natural language processing (NLP) have been
driven by the emergence of large language models (LLMs), which have significantly …

With the rapid progress in Natural Language Processing (NLP), Pre-trained Language
Models (PLM) such as BERT, BioBERT, and ChatGPT have shown great potential in various …

Pre-trained language models (PLMs) have been the de facto paradigm for most natural
language processing tasks. This also benefits the biomedical domain: researchers from …

Generalized language models that are pre-trained with a large corpus have achieved great
performance on natural language tasks. While many pre-trained transformers for English are …

Pretraining large neural language models, such as BERT, has led to impressive gains on
many natural language processing (NLP) tasks. However, most pretraining efforts focus on …

This work presents the first large-scale biomedical Spanish language models trained from
scratch, using large biomedical corpora consisting of a total of 1.1 B tokens and an EHR …

Medical text classification organizes medical documents into categories to streamline
information retrieval and support clinical decision-making. Traditional machine learning …

Research on language technology for the development of medical applications is currently a
hot topic in Natural Language Understanding and Generation. Thus, a number of large …