Knowledge Representation and Management: Interest in New Solutions for Ontology Curation.


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 2021
Historique:
entrez: 3 9 2021
pubmed: 4 9 2021
medline: 2 10 2021
Statut: ppublish

Résumé

To select, present and summarize some of the best papers in the field of Knowledge Representation and Management (KRM) published in 2020. A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers of KRM published in 2020, based on PubMed queries. This review was conducted according to the IMIA Yearbook guidelines. Four best papers were selected among 1,175 publications. In contrast with the papers selected last year, the four best papers of 2020 demonstrated a significant focus on methods and tools for ontology curation and design. The usual KRM application domains (bioinformatics, machine learning, and electronic health records) were also represented. In 2020, ontology curation emerges as a significant topic of research interest. Bioinformatics, machine learning, and electronics health records remain significant research areas in the KRM community with various applications. Knowledge representations are key to advance machine learning by providing context and to develop novel bioinformatics metrics. As in 2019, representations serve a great variety of applications across many medical domains, with actionable results and now with growing adhesion to the open science initiative.

Identifiants

pubmed: 34479390
doi: 10.1055/s-0041-1726508
pmc: PMC8416227
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

185-190

Informations de copyright

IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Déclaration de conflit d'intérêts

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

Références

Am J Hum Genet. 2020 Sep 3;107(3):403-417
pubmed: 32755546
Nucleic Acids Res. 2020 Jan 8;48(D1):D704-D715
pubmed: 31701156
PLoS One. 2020 May 27;15(5):e0233438
pubmed: 32459809
Yearb Med Inform. 2017 Aug;26(1):148-151
pubmed: 29063556
J Am Med Inform Assoc. 2020 Oct 1;27(10):1568-1575
pubmed: 32918476
J Med Internet Res. 2020 Dec 11;22(12):e23721
pubmed: 33306032
Brief Bioinform. 2021 Jul 20;22(4):
pubmed: 33049044
PLoS One. 2020 Jul 9;15(7):e0235670
pubmed: 32645039
BMC Bioinformatics. 2020 Jan 3;21(1):6
pubmed: 31900127
Yearb Med Inform. 2020 Aug;29(1):163-168
pubmed: 32823311
Yearb Med Inform. 2018 Aug;27(1):140-145
pubmed: 30157517
Appl Clin Inform. 2020 Jan;11(1):13-22
pubmed: 31914471
Math Biosci Eng. 2020 Jun 8;17(4):4098-4114
pubmed: 32987570
BMC Med Inform Decis Mak. 2020 Dec 15;20(Suppl 10):311
pubmed: 33319712
PLoS Biol. 2020 Jan 23;18(1):e3000583
pubmed: 31971940
J Am Med Inform Assoc. 2020 Nov 1;27(11):1648-1657
pubmed: 32935127
Nucleic Acids Res. 2020 Jan 8;48(D1):D933-D940
pubmed: 31612961
BMC Med Inform Decis Mak. 2020 Mar 4;20(1):47
pubmed: 32131804
Yearb Med Inform. 2019 Aug;28(1):152-155
pubmed: 31419827

Auteurs

Ferdinand Dhombres (F)

Sorbonne Université, INSERM, Univ Sorbonne Paris Nord, LIMICS, Paris, France.
Sorbonne Université, Service de Médecine Fœtale, DMU Origyne, AP-HP, Hôpital Armand Trousseau, Paris, France.

Jean Charlet (J)

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

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Classifications MeSH