ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2018
Standardizing Heterogeneous Annotation Corpora Using HL7 FHIR for Facilitating their Reuse and Integration in Clinical NLP.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Electronic Health Record and Semantic Issues Using Fast Healthcare Interoperability Resources: Systematic Mapping Review.Journal of medical Internet research · 2024Pooled it
- State-of-the-Art Fast Healthcare Interoperability Resources (FHIR)-Based Data Model and Structure Implementations: Systematic Scoping Review.JMIR medical informatics · 2024Article
- HL7 FHIR-based tools and initiatives to support clinical research: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- A Framework (SOCRATex) for Hierarchical Annotation of Unstructured Electronic Health Records and Integration Into a Standardized Medical Database: Development and Usability Study.JMIR medical informatics · 2021Article
- Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing.Methods of information in medicine · 2020Article
- Developing an FHIR-Based Computational Pipeline for Automatic Population of Case Report Forms for Colorectal Cancer Clinical Trials Using Electronic Health Records.JCO clinical cancer informatics · 2020Article
- Article
- Developing a FHIR-based EHR phenotyping framework: A case study for identification of patients with obesity and multiple comorbidities from discharge summaries.Journal of biomedical informatics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Manually annotated clinical corpora are commonly used as the gold standards for the training and evaluation of clinical natural language processing (NLP) tools. The creation of these manual annotation corpora, however, is both costly and time-consuming. There is an emerging need in the clinical NLP community for reusing existing annotation corpora across different clinical NLP tasks. The objective of this study is to design, develop and evaluate a framework and accompanying tools to support the standardization and integration of annotation corpora using the HL7 Fast Healthcare Interoperability Resources (FHIR) specification. The framework contains two main modules: 1) an automatic schema transformation module, in which the annotation schema in each corpus is automatically transformed into the FHIR-based schema; 2) an expert-based verification and annotation module, in which existing annotations can be verified and new annotations can be added for new elements defined in FHIR. We evaluated the framework using various annotation corpora created as part of different clinical NLP projects at the Mayo Clinic. We demonstrated that it is feasible to leverage FHIR as a standard data model for standardizing heterogeneous annotation corpora for their reuse and integration in advanced clinical NLP research and practices.
Indexed as
Identifiers
30815098PMC6371380What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.