3260 papers • 126 benchmarks • 313 datasets
PICO recognition is an information extraction task for identifying Participant, Intervention, Comparator, and Outcome (PICO elements) information from clinical literature.
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SciBERT leverages unsupervised pretraining on a large multi-domain corpus of scientific publications to improve performance on downstream scientific NLP tasks and demonstrates statistically significant improvements over BERT.
A corpus of 5,000 richly annotated abstracts of medical articles describing clinical randomized controlled trials is presented and a set of challenging NLP tasks that would aid searching of the medical literature and the practice of evidence-based medicine are outlined.
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