Case Report: Electronic Screening Improves Efficiency in Clinical Trial Recruitment

By Samir R. Thadani, Chunhua Weng, J. Bigger, J. Ennever, David Wajngurt. 2009

127 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Public Health, Environmental and Occupational Health, Statistics and Probability

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Citations in the corpus

Natural Language Processing for EHR-Based Computational Phenotyping (2018, background): “ment, and automated querying over trials can support clinical knowledge curation [55].”
Defining and measuring completeness of electronic health records for secondary use (2013, unknown): “EHR-based cohort identification and phenotyping, for example, often utilize some combination of diagnoses, laboratory results, medications, and procedure codes [21–23].”
Electronic health records to facilitate clinical research (2016, background): “However, incomplete data may prohibit screening for the complete list of eligibility criteria [34], but EHRs may facilitate pre-screening of patients by age, gender, and diagnosis, particularly for exclusion of ineligible patients, and reduce the overall screening burden in clinical trials [35].”
Bridging semantics and syntax with graph algorithms - state-of-the-art of extracting biomedical relations (2017, background): “Electronic screening can improve efficiency in clinical trial recruitment, and intelligent query over trials can support clinical knowledge curation [33].”
Bridging semantics and syntax with graph algorithms —state-of-the-art of extracting biomedical relations (2015, background): “Electronic screening can improve efficiency in clinical trial recruitment, and intelligent query over trials can support clinical knowledge curation [28].”
EliXR: an approach to eligibility criteria extraction and representation (2011, methodology): “The limitations of such a manual process are: (1) it is costly and laborious; (2) it requires deep domain knowledge to understand the proper and specific relation between concepts and the ability to recognize implicit relations in text;(30) and (3) it is not easily scalable to a larger dataset.”