EliXR: an approach to eligibility criteria extraction and representation
By Chunhua Weng, Xiaoying Wu, Zhihui Luo, Mary Regina Boland, Dimitri Theodoratos, Stephen B. Johnson. 2011
153 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Health Information Management, Molecular Biology
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Citations in the corpus
- Natural Language Processing for EHR-Based Computational Phenotyping (2018, background): “…are expected to be a promising direction for future research; especially for the tasks of extracting clinical trial eligibility criteria [195], representing test results for automating diagnosis categorization [108], and building pharmacogenomic semantic networks [58], where the number…”
- Bridging semantics and syntax with graph algorithms - state-of-the-art of extracting biomedical relations (2017, methodology): “[36] In-house parser Frequent subtree pattern mining to construct relations”
- Bridging semantics and syntax with graph algorithms —state-of-the-art of extracting biomedical relations (2015, methodology): “However, there is a gap between the technical advances and the demands from many real-world tasks, including building pharmacogenomics semantic networks [35], extracting clinical trial eligibility criteria [32] and representing test results for automating diagnosis categorization [44,45].”
- Clinical Information Extraction Applications: A Literature Review (2017, background): “Fourth, the articles utilizing clinical narratives from non-EHR systems, such as clinical trials [184], are not”