RT Journal Article
T1 Automated semantic annotation of rare disease cases: a case study
A1 Taboada Iglesias, María Jesús
A1 Rodríguez Castiñeira, Hadriana
A1 Martínez Hernández, Diego
A1 Pardo Parrado, María
A1 Sobrido Gómez, María Jesús
K1 Cerebrotendinous xanthomatosis
K1 Rare disease
K1 Genetic sequencing technologies
AB Motivation: As the number of clinical reports in the peer-reviewed medical literature keeps growing, there is an increasing need for online search tools to find and analyze publications on patients with similar clinical characteristics. This problem is especially critical and challenging for rare diseases, where publications of large series are scarce. Through an applied example, we illustrate how to automatically identify new relevant cases and semantically annotate the relevant literature about patient case reports to capture the phenotype of a rare disease named cerebrotendinous xanthomatosis.Results: Our results confirm that it is possible to automatically identify new relevant case reports with a high precision and to annotate them with a satisfactory quality (74% F-measure). Automated annotation with an emphasis to entirely describe all phenotypic abnormalities found in a disease may facilitate curation efforts by supplying phenotype retrieval and assessment of their frequency
PB Oxford Univesity Press
YR 2014
FD 2014
LK http://hdl.handle.net/10347/21797
UL http://hdl.handle.net/10347/21797
LA eng
NO Maria Taboada, Hadriana Rodríguez, Diego Martínez, María Pardo, María Jesús Sobrido, Automated semantic annotation of rare disease cases: a case study, Database, Volume 2014, 2014, bau045, https://doi.org/10.1093/database/bau045
NO National Institute of Health Carlos III (grant no. FIS2012-PI12/00373: OntoNeurophen). Funding for open access charge: National Institute of Health Carlos III (grant no. FIS2012-PI12/00373)
DS Minerva
RD 24 abr 2026