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The openEHR Genomics Project.
Mascia, Cecilia; Frexia, Francesca; Uva, Paolo; Zanetti, Gianluigi; Pireddu, Luca; Giacomelli, Gideon; Jaeger-Schmidt, Christina; Tomczak, Aurelie; Schumacher, Simon; Kraecher, Florian; Eils, Roland; Ljosland Bakke, Silje; Leslie, Heather.
Afiliação
  • Mascia C; CRS4: Center for Advanced Studies, Research and Development in Sardinia.
  • Frexia F; CRS4: Center for Advanced Studies, Research and Development in Sardinia.
  • Uva P; CRS4: Center for Advanced Studies, Research and Development in Sardinia.
  • Zanetti G; CRS4: Center for Advanced Studies, Research and Development in Sardinia.
  • Pireddu L; CRS4: Center for Advanced Studies, Research and Development in Sardinia.
  • Giacomelli G; HiGHmed Consortium.
  • Jaeger-Schmidt C; HiGHmed Consortium.
  • Tomczak A; HiGHmed Consortium.
  • Schumacher S; Institute of Pathology, University Hospital Heidelberg.
  • Kraecher F; HiGHmed Consortium.
  • Eils R; HiGHmed Consortium.
  • Ljosland Bakke S; HiGHmed Consortium.
  • Leslie H; Clinical Model program, openEHR Foundation.
Stud Health Technol Inform ; 270: 443-447, 2020 Jun 16.
Article em En | MEDLINE | ID: mdl-32570423
ABSTRACT
Current high-throughput sequencing technologies allow us to acquire entire genomes in a very short time and at a relatively sustainable cost, thus resulting in an increasing diffusion of genetic test capabilities, in specialized clinical laboratories and research centers. In contrast, it is still limited the impact of genomic information on clinical decisions, as an effective interpretation is a challenging task. From the technological point of view, genomic data are big in size, have a complex granular nature and strongly depend on the computational steps of the generation and processing workflows. This article introduces our work to create the openEHR Genomic Project and the set of genomic information models we developed to catch such complex structure and to preserve data provenance efficiently in a machine-readable format. The models support clinical actionability of data, by improving their quality, fostering interoperability and laying the basis for re-usability.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genômica / Registros Eletrônicos de Saúde Tipo de estudo: Prognostic_studies Idioma: En Revista: Stud Health Technol Inform Assunto da revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genômica / Registros Eletrônicos de Saúde Tipo de estudo: Prognostic_studies Idioma: En Revista: Stud Health Technol Inform Assunto da revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Ano de publicação: 2020 Tipo de documento: Article