Text-Mining Services of the Swiss Variant Interpretation Platform for Oncology
| Autor: | Caucheteur, Déborah, Gobeill, Julien, Mottaz, Anaïs, Pasche, Emilie, Michel, Pierre-André, Mottin, Luc, Stekhoven, Daniel J., Barbié, Valérie, Ruch, Patrick |
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| Přispěvatelé: | Pape-Haugaard, Louise B., Lovis, Christian, Cort Madsen, Inge, Weber, Patrick, Hostrup Nielsen, Per, Scott, Philip |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Studies in Health Technology and Informatics, 270 Digital Personalized Health and Medicine |
| ISSN: | 0926-9630 1879-8365 |
| DOI: | 10.3929/ethz-b-000424123 |
| Popis: | The Swiss Variant Interpretation Platform for Oncology is a centralized, joint and curated database for clinical somatic variants piloted by a board of Swiss healthcare institutions and operated by the SIB Swiss Institute of Bioinformatics. To support this effort, SIB Text Mining designed a set of text analytics services. This report focuses on three of those services. First, the automatic annotations of the literature with a set of terminologies have been performed, resulting in a large annotated version of MEDLINE and PMC. Second, a generator of variant synonyms for single nucleotide variants has been developed using publicly available data resources, as well as patterns of non-standard formats, often found in the literature. Third, a literature ranking service enables to retrieve a ranked set of MEDLINE abstracts given a variant and optionally a diagnosis. The annotation of MEDLINE and PMC resulted in a total of respectively 785,181,199 and 1,156,060,212 annotations, which means an average of 26 and 425 annotations per abstract and full-text article. The generator of variant synonyms enables to retrieve up to 42 synonyms for a variant. The literature ranking service reaches a precision (P10) of 63%, which means that almost two-thirds of the top-10 returned abstracts are judged relevant. Further services will be implemented to complete this set of services, such as a service to retrieve relevant clinical trials for a patient and a literature ranking service for full-text articles. Studies in Health Technology and Informatics, 270 ISSN:0926-9630 ISSN:1879-8365 Digital Personalized Health and Medicine ISBN:978-1-64368-082-8 ISBN:978-1-64368-083-5 |
| Databáze: | OpenAIRE |
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