@inproceedings{8d611db616b042d889f8e1884d623902,
title = "Evaluation of Criteria2Query: Towards Augmented Intelligence for Cohort Identification",
abstract = "Electronic healthcare records data promises to improve the efficiency of patient eligibility screening, which is an important factor in the success of clinical trials and observational studies. To bridge the sociotechnical gap in cohort identification by end-users, who are clinicians or researchers unfamiliar with underlying EHR databases, we previously developed a natural language query interface named Criteria2Query (C2Q) that automatically transforms free-text eligibility criteria to executable database queries. In this study, we present a comprehensive evaluation of C2Q to generate more actionable insights to inform the design and evaluation of future natural language user interfaces for clinical databases, towards the realization of Augmented Intelligence (AI) for clinical cohort definition via e-screening.",
keywords = "Artificial Intelligence (AI), Clinical Trial, Natural Language Processing",
author = "Cong Liu and Hao Liu and Casey Ta and James Roger and Alex Butler and Junghwan Lee and Jaehyun Kim and Ning Shang and Chunhua Weng",
note = "Publisher Copyright: {\textcopyright} 2022 International Medical Informatics Association (IMIA) and IOS Press.; 18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021 ; Conference date: 02-10-2021 Through 04-10-2021",
year = "2022",
month = jun,
day = "6",
doi = "10.3233/SHTI220082",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "297--300",
editor = "Paula Otero and Philip Scott and Martin, \{Susan Z.\} and Elaine Huesing",
booktitle = "MEDINFO 2021",
}