Biomedical Corpus

Biomedical corpora are large collections of text and data from the biomedical literature used to train and evaluate natural language processing (NLP) models. Current research focuses on developing and improving these models, particularly large language models (LLMs) and transformer-based architectures, for tasks like entity recognition, relation extraction, question answering, and text generation within the biomedical domain. This work aims to improve the accuracy and efficiency of information extraction from biomedical texts, ultimately facilitating advancements in drug discovery, disease understanding, and personalized medicine. Challenges remain in addressing biases, ensuring factual accuracy, and handling the complexities of multilingual and low-resource languages within these corpora.