NegBio: a high-performance tool for negation and uncertainty detection in radiology reports

Negative and uncertain medical findings are frequent in radiology reports, discriminating them from positive findings remains challenging for extraction. Here, we propose a new algorithm, NegBio, to detect and uncertain findings in radiology reports. Unlike previous-based methods, NegBio utilizes patterns on universal dependencies to the scope of triggers that are indicative of negation or uncertainty. evaluated NegBio on four datasets, including two public benchmarking corpora radiology reports, a new radiology corpus that we annotated for this work, a public corpus of general clinical texts. Evaluation on these datasets that NegBio is highly accurate for detecting negative and findings and compares favorably to a widely-used state-of-the-art NegEx (an average of 9. 5% improvement in precision and 5. 1% in1-score).