Medical Corpus

Medical corpora are collections of textual medical data used to train and evaluate natural language processing (NLP) models for various healthcare applications. Current research focuses on developing larger, multilingual corpora, improving data cleaning techniques (e.g., using ensemble methods), and employing retrieval-augmented generation (RAG) and transformer-based models like BERT and LLMs (including fine-tuning on medical data) to enhance accuracy and address challenges like hallucinations and outdated information. These advancements are crucial for improving medical information retrieval, question answering, clinical text simplification, and other tasks, ultimately leading to more efficient and effective healthcare practices.