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1.
Stud Health Technol Inform ; 310: 1388-1389, 2024 Jan 25.
Artigo em Inglês | MEDLINE | ID: mdl-38269660

RESUMO

Medical images need annotations with high-level semantic descriptors, so that domain experts can search for the desired dataset among an enormous volume of visual media within a Medical Data Integration Center. This article introduces a processing pipeline for storing and annotating DICOM and PNG imaging data by applying Elasticsearch, S3 and Deep Learning technologies. The proposed method processes both DICOM and PNG images to generate annotations. These image annotations are indexed in Elasticsearch with the corresponding raw data paths, where they can be retrieved and analyzed.


Assuntos
Hospitais , Semântica , Tecnologia
2.
Stud Health Technol Inform ; 310: 1464-1465, 2024 Jan 25.
Artigo em Inglês | MEDLINE | ID: mdl-38269698

RESUMO

The era of the electronic health record (EHR) requires lots of semantic interoperability for data sharing and reusability. We select HL7 v2 messages as the most common structured data type in hospital information systems, to investigate the plausibility of using Elasticsearch (ES) as a healthcare search engine and data analytics tool. Due to the facts, Elasticsearch can be integrated as a powerful searchable database for practical healthcare applications, to analyze structured healthcare data from various locations. It allows easy and efficient searching for complex query tasks.


Assuntos
Ciência de Dados , Sistemas de Informação Hospitalar , Bases de Dados Factuais , Registros Eletrônicos de Saúde , Instalações de Saúde
3.
Stud Health Technol Inform ; 299: 151-156, 2022 Nov 03.
Artigo em Inglês | MEDLINE | ID: mdl-36325856

RESUMO

Improving the interoperability of healthcare information systems is a crucial clinical care issue involving disparate but coexisting information systems. However, healthcare organizations are also facing the dilemma of choosing the right ETL tool and architecture pattern as data warehouse enterprises. This article gives an overview of current ETL tools for healthcare data integration. In addition, we demonstrate three ETL processes for clinical data integration using different ETL tools and architecture patterns, which map data from various data sources (e.g. MEONA and ORBIS) to diverse standards (e.g. FHIR and openEHR). Depending on the project's technical requirements, we choose our ETL tool and software architecture pattern to boost team efficiency.


Assuntos
Data Warehousing , Registros Eletrônicos de Saúde , Armazenamento e Recuperação da Informação , Software , Atenção à Saúde
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