Researchers have introduced "Structured PubMed," a large dataset containing over 23.2 million biomedical abstracts from PubMed. This dataset aims to improve information retrieval and text mining by providing section-labeled abstracts. It includes both author-structured abstracts and those automatically labeled using a Large Language Model pipeline, offering a valuable resource for training classification models and benchmarking text-segmentation architectures. AI
IMPACT Enables more precise information extraction and knowledge synthesis from biomedical literature.
RANK_REASON The cluster contains a research paper detailing a new dataset.
Read on arXiv cs.IR (Information Retrieval) →
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