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Review
. 2020 Aug;29(1):163-168.
doi: 10.1055/s-0040-1702010. Epub 2020 Aug 21.

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

Ferdinand Dhombres  1   2 , Jean Charlet  1   3 ; Section Editors for the IMIA Yearbook Section on Knowledge Representation and Management
Affiliations
Review

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

Ferdinand Dhombres et al. Yearb Med Inform. 2020 Aug.

Abstract

Objective: To select, present, and summarize the best papers in the field of Knowledge Representation and Management (KRM) published in 2019.

Methods: 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.

Results: 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.

Conclusion: 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.

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Conflict of interest statement

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

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References

    1. Dhombres F, Charlet J. Formal Medical Knowledge Representation Supports Deep Learning Algorithms, Bioinformatics Pipelines, Genomics Data Analysis, and Big Data Processes. Yearb Med Inform. 2019;28(01):152–5. - PMC - PubMed
    1. Dhombres F, Charlet J. As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018. Yearb Med Inform. 2018;27(01):140–5. - PMC - PubMed
    1. Dhombres F, Charlet J. Knowledge Representation and Management, It’s Time to Integrate. Yearb Med Inform. 2017;26(01):148–51. - PMC - PubMed
    1. Burek P, Scherf N, Herre H. Ontology patterns for the representation of quality changes of cells in time. J Biomed Semantics. 2019;10(01):16. - PMC - PubMed
    1. Denaxas S, Gonzalez-Izquierdo A, Direk K, Fitzpatrick N K, Fatemifar G, Banerjee A et al.UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER. J Am Med Inform Assoc. 2019;26(12):1545–59. - PMC - PubMed