Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
Designing an openEHR-Based Pipeline for Extracting and Standardizing Unstructured Clinical Data Using Natural Language Processing ; volume:59 ; number:S 02 ; year:2020 ; pages:e64-e78 ; 02
Methods of information in medicine ; 59, Heft S 02 (2020), e64-e78, 02
- Contributor
- DOI
-
10.1055/s-0040-1716403
- URN
-
urn:nbn:de:101:1-2021021112273564645584
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:30 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Wulff, Antje
- Mast, Marcel
- Hassler, Marcus
- Montag, Sara
- Marschollek, Michael
- Jack, Thomas
Other Objects (12)
Forecasting news-related liquidity shocks: extracting signals from unstructured data
Designing Functional Data Pipelines for Reproducibility and Maintainability
A graph-based approach for designing extensible pipelines
The Fine-Tuned Large Language Model for Extracting the Progressive Bone Metastasis from Unstructured Radiology Reports
Artificial intelligence and corporate reporting: Extracting information from unstructured data with deep learning and natural language processing
Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples
A high-throughput pipeline for designing microarray-based pathogen diagnostic assays
A hybrid solution for extracting structured medical information from unstructured data in medical records via a double-reading/entry system
Structured and Unstructured Valuation
Tides on unstructured meshes
Making sense of unstructured data
Knowledge extraction from unstructured data
Forecasting news-related liquidity shocks: extracting signals from unstructured data
Designing Functional Data Pipelines for Reproducibility and Maintainability
A graph-based approach for designing extensible pipelines
The Fine-Tuned Large Language Model for Extracting the Progressive Bone Metastasis from Unstructured Radiology Reports
Artificial intelligence and corporate reporting: Extracting information from unstructured data with deep learning and natural language processing
Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples
A high-throughput pipeline for designing microarray-based pathogen diagnostic assays
A hybrid solution for extracting structured medical information from unstructured data in medical records via a double-reading/entry system
Structured and Unstructured Valuation
Tides on unstructured meshes
Making sense of unstructured data
Knowledge extraction from unstructured data
Forecasting news-related liquidity shocks: extracting signals from unstructured data
Designing Functional Data Pipelines for Reproducibility and Maintainability
A graph-based approach for designing extensible pipelines
The Fine-Tuned Large Language Model for Extracting the Progressive Bone Metastasis from Unstructured Radiology Reports
Artificial intelligence and corporate reporting: Extracting information from unstructured data with deep learning and natural language processing
Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples
A high-throughput pipeline for designing microarray-based pathogen diagnostic assays
A hybrid solution for extracting structured medical information from unstructured data in medical records via a double-reading/entry system
Structured and Unstructured Valuation
Tides on unstructured meshes
Making sense of unstructured data