BioNER Datasets

Biomedical Named Entity Recognition (BioNER) datasets are crucial for developing systems that automatically identify key entities (genes, diseases, etc.) within biomedical text. Current research focuses on addressing data scarcity through techniques like transfer learning from general-domain resources and data augmentation methods, often employing neural network architectures such as sequence labeling models (e.g., using CRFs) and span prediction models. These advancements aim to improve the accuracy and robustness of BioNER systems, ultimately facilitating more efficient analysis of biomedical literature and accelerating scientific discovery. Furthermore, research is expanding into multimodal BioNER, integrating visual information with text to improve entity recognition and grounding.