Evaluation of Criteria2Query: Towards Augmented Intelligence for Cohort Identification.
Stud Health Technol Inform
; 290: 297-300, 2022 Jun 06.
Article
em En
| MEDLINE
| ID: mdl-35673021
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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Linguagem Natural
/
Inteligência Artificial
Tipo de estudo:
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Stud Health Technol Inform
Assunto da revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Estados Unidos