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As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018
Objectives: To select, present, and summarize the best papers published in 2017 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers of KRM published...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6115232/ https://www.ncbi.nlm.nih.gov/pubmed/30157517 http://dx.doi.org/10.1055/s-0038-1667078 |
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author | Dhombres, Ferdinand Charlet, Jean |
author_facet | Dhombres, Ferdinand Charlet, Jean |
author_sort | Dhombres, Ferdinand |
collection | PubMed |
description | Objectives: To select, present, and summarize the best papers published in 2017 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers of KRM published in 2017, based on a PubMed query. Results: In direct line with the research on data integration presented in the KRM section of the 2017 edition of the International Medical Informatics Association (IMIA) Yearbook, the five best papers for 2018 demonstrate even further the added-value of ontology-based integration approaches for phenotype-genotype association mining. Additionally, among the 15 preselected papers, two aspects of KRM are in the spotlight: the design of knowledge bases and new challenges in using ontologies. Conclusions: Ontologies are demonstrating their maturity to integrate medical data and begin to support clinical practices. New challenges have emerged: the query on distributed semantically annotated datasets, the efficiency of semantic annotation processes, the semantic representation of large textual datasets, the control of biases associated with semantic annotations, and the computation of Bayesian indicators on data annotated with ontologies. |
format | Online Article Text |
id | pubmed-6115232 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Georg Thieme Verlag KG |
record_format | MEDLINE/PubMed |
spelling | pubmed-61152322019-04-01 As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018 Dhombres, Ferdinand Charlet, Jean Yearb Med Inform Objectives: To select, present, and summarize the best papers published in 2017 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed to select the most interesting papers of KRM published in 2017, based on a PubMed query. Results: In direct line with the research on data integration presented in the KRM section of the 2017 edition of the International Medical Informatics Association (IMIA) Yearbook, the five best papers for 2018 demonstrate even further the added-value of ontology-based integration approaches for phenotype-genotype association mining. Additionally, among the 15 preselected papers, two aspects of KRM are in the spotlight: the design of knowledge bases and new challenges in using ontologies. Conclusions: Ontologies are demonstrating their maturity to integrate medical data and begin to support clinical practices. New challenges have emerged: the query on distributed semantically annotated datasets, the efficiency of semantic annotation processes, the semantic representation of large textual datasets, the control of biases associated with semantic annotations, and the computation of Bayesian indicators on data annotated with ontologies. Georg Thieme Verlag KG 2018-08 2018-08-29 /pmc/articles/PMC6115232/ /pubmed/30157517 http://dx.doi.org/10.1055/s-0038-1667078 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited. |
spellingShingle | Dhombres, Ferdinand Charlet, Jean As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018 |
title | As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018 |
title_full | As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018 |
title_fullStr | As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018 |
title_full_unstemmed | As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018 |
title_short | As Ontologies Reach Maturity, Artificial Intelligence Starts Being Fully Efficient: Findings from the Section on Knowledge Representation and Management for the Yearbook 2018 |
title_sort | as ontologies reach maturity, artificial intelligence starts being fully efficient: findings from the section on knowledge representation and management for the yearbook 2018 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6115232/ https://www.ncbi.nlm.nih.gov/pubmed/30157517 http://dx.doi.org/10.1055/s-0038-1667078 |
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