COVID 19 Literature

COVID-19 research literature analysis focuses on efficiently extracting and organizing information from the massive volume of published articles. Current research emphasizes leveraging large language models (LLMs), particularly transformer-based architectures like BERT and its variants, for tasks such as named entity recognition, question answering, and multi-label topic classification. These methods aim to improve knowledge retrieval and accelerate the translation of research findings into clinical practice, ultimately enhancing healthcare responses to pandemics and similar large-scale health crises. The development and application of these advanced NLP techniques are crucial for managing the information overload inherent in rapidly evolving research fields.