This study aims to build a natural language processing system to transform eligibility criteria text into standards-based cohort identification queries that are ...
This study aims to build a natural language processing system to transform eligibility criteria text into standards-based cohort identification queries that ...
Feb 7, 2019 · We present Criteria2Query, a novel NLI for transforming free-text clinical research criteria to OMOP CDM-based cohort queries. It ...
Criteria2Query: Automatically Transforming Clinical Research Eligibility Criteria Text to OMOP Common Data Model (CDM)-based Cohort Queries. by Tian Kang.
Criteria2Query (C2Q) is an NLP pipeline for automating the translation of clinical trial eligibility criteria into executable cohort queries formatted using the ...
Missing: Transforming Text
Criteria2Query (C2Q) is an automatic cohort identification system. It enhances human-computer collaboration to convert complex eligibility criteria text ...
Missing: Transforming Research
Criteria2Query: Automatically Transforming Clinical Research Eligibility Criteria Text to OMOP. Common Data Model (CDM)-based Cohort Queries. Criteriq2Query ...
Apr 11, 2023 · Criteria2Query: Automatically Transforming Clinical Research Eligibility Criteria Text to OMOP Common Data Model (CDM)-based Cohort Queries.
Consultations for parsing free-text inclusion/exclusion criteria and produce a structured cohort definition query that can be executed against an ...
Missing: Automatically Transforming
[36] created an annotated corpus of eligibility criteria from 700 COVID-19 trials, to facilitate searching COVID-19 trials and developing machine learning-based ...