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García del Valle, Eduardo Pantaleón and Lagunes García, Gerardo and Prieto Santamaría, Lucía and Zanin, Massimiliano and Rodríguez González, Alejandro and Menasalvas Ruiz, Ernestina (2019). Completing missing MeSH code mappings in UMLS through alternative expert-curated sources. In: "32nd International Symposium on Computer-Based Medical Systems (CBMS)", 05-07 Jun 2019, Cordoba, España. pp. 174-179. https://doi.org/10.1109/CBMS.2019.00044.
Title: | Completing missing MeSH code mappings in UMLS through alternative expert-curated sources |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | 32nd International Symposium on Computer-Based Medical Systems (CBMS) |
Event Dates: | 05-07 Jun 2019 |
Event Location: | Cordoba, España |
Title of Book: | 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS) |
Date: | 2019 |
Subjects: | |
Freetext Keywords: | Disease classification, Disease code mapping, MeSH, ICD-10, SNOMED CT, UMLS |
Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
Department: | Lenguajes y Sistemas Informáticos e Ingeniería del Software |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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The increasing availability of biological, clinical and literary sources enables the study of diseases from a more comprehensive approach. However, the interoperability of these sources, particularly of the codes used to identify diseases, poses a major challenge. Because of its role as a hub of multiple medical vocabularies, the Unified Medical Language System (UMLS) has become one of the most widely used resources for mapping diseases from different classification systems. The coverage of these mappings, nevertheless, is still insufficient, so researchers must resort to other methods to fill these gaps. In this article we analyze the limitations in UMLS mappings for the MeSH, ICD-10 and SNOMED CT vocabularies and propose the exploitation of alternative expert-curated sources to complete it. As a result, we demonstrate that this approach allows resolving more than 50% of the missing mappings for these vocabularies. All the findings are shared for validation and reuse.
Type | Code | Acronym | Leader | Title |
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Horizon 2020 | 727658 | IASIS | National Center for Scientific Research DEMOKRITOS | Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients |
Item ID: | 66941 |
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DC Identifier: | https://oa.upm.es/66941/ |
OAI Identifier: | oai:oa.upm.es:66941 |
DOI: | 10.1109/CBMS.2019.00044 |
Official URL: | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8787463 |
Deposited by: | Memoria Investigacion |
Deposited on: | 07 May 2021 05:54 |
Last Modified: | 07 May 2021 05:54 |