Design and Use of Semantic Resources: Findings from the Section on Knowledge Representation and Management of the 2020 International Medical Informatics Association Yearbook.


Journal

Yearbook of medical informatics
ISSN: 2364-0502
Titre abrégé: Yearb Med Inform
Pays: Germany
ID NLM: 9312666

Informations de publication

Date de publication:
Aug 2020
Historique:
entrez: 22 8 2020
pubmed: 22 8 2020
medline: 17 4 2021
Statut: ppublish

Résumé

To select, present, and summarize the best papers in the field of Knowledge Representation and Management (KRM) published in 2019. A comprehensive and standardized review of the biomedical informatics literature was performed to select the most interesting papers of KRM published in 2019, based on PubMed and ISI Web Of Knowledge queries. Four best papers were selected among 1,189 publications retrieved, following the usual International Medical Informatics Association Yearbook reviewing process. In 2019, research areas covered by pre-selected papers were represented by the design of semantic resources (methods, visualization, curation) and the application of semantic representations for the integration/enrichment of biomedical data. Besides new ontologies and sound methodological guidance to rethink knowledge bases design, we observed large scale applications, promising results for phenotypes characterization, semantic-aware machine learning solutions for biomedical data analysis, and semantic provenance information representations for scientific reproducibility evaluation. In the KRM selection for 2019, research on knowledge representation demonstrated significant contributions both in the design and in the application of semantic resources. Semantic representations serve a great variety of applications across many medical domains, with actionable results.

Identifiants

pubmed: 32823311
doi: 10.1055/s-0040-1702010
pmc: PMC7442529
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

163-168

Informations de copyright

Georg Thieme Verlag KG Stuttgart.

Déclaration de conflit d'intérêts

Disclosure The authors report no conflicts of interest in this work.

Références

BMC Genomics. 2019 Jul 16;20(Suppl 8):548
pubmed: 31307376
Yearb Med Inform. 2018 Aug;27(1):140-145
pubmed: 30157517
J Biomed Semantics. 2019 Jul 15;10(1):13
pubmed: 31307550
J Biomed Semantics. 2019 Jan 18;10(1):3
pubmed: 30658684
Yearb Med Inform. 2017 Aug;26(1):148-151
pubmed: 29063556
Yearb Med Inform. 2019 Aug;28(1):152-155
pubmed: 31419827
J Am Med Inform Assoc. 2019 Dec 1;26(12):1545-1559
pubmed: 31329239
J Biomed Semantics. 2019 Oct 16;10(1):16
pubmed: 31619282
Bioinformatics. 2020 Apr 1;36(7):2229-2236
pubmed: 31821406
BMC Med Inform Decis Mak. 2019 Feb 14;19(1):32
pubmed: 30764825
Int J Med Inform. 2019 Jan;121:10-18
pubmed: 30545485
BMC Bioinformatics. 2019 May 1;20(Suppl 7):199
pubmed: 31074377
BMC Bioinformatics. 2019 Jul 29;20(1):407
pubmed: 31357927
JMIR Ment Health. 2019 May 21;6(5):e13498
pubmed: 31115344
BMC Bioinformatics. 2019 Jan 7;20(1):10
pubmed: 30616557
Database (Oxford). 2019 Jan 1;2019:
pubmed: 31225582
BMC Bioinformatics. 2019 Feb 18;20(1):84
pubmed: 30777018

Auteurs

Ferdinand Dhombres (F)

Sorbonne Université, Université Paris Nord, INSERM, UMR_S 1142, LIMICS, Paris, France.
Médecine Sorbonne Université, Service de Médecine Fœtale, Hôpital Armand Trousseau, Paris, France.

Jean Charlet (J)

Sorbonne Université, Université Paris Nord, INSERM, UMR_S 1142, LIMICS, Paris, France.
AP-HP, DRCI, Paris, France.

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Classifications MeSH