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of 17
pro vyhledávání: '"ARGUELLO CASTELEIRO, Mercedes"'
Autor:
Arguello Casteleiro, Mercedes, Des Diz, Julio, Maroto, Nava, Fernandez Prieto, Maria Jesus, Peters, Simon, Wroe, Chris, Sevillano Torrado, Carlos, Maseda Fernandez, Diego, Stevens, Robert
Publikováno v:
JMIR Medical Informatics, Vol 8, Iss 8, p e16948 (2020)
BackgroundHow to treat a disease remains to be the most common type of clinical question. Obtaining evidence-based answers from biomedical literature is difficult. Analogical reasoning with embeddings from deep learning (embedding analogies) may extr
Externí odkaz:
https://doaj.org/article/7f53cca3cac14f939f17ef3eb8630e3f
Autor:
Davies, Heather, Nenadic, Goran, Alfattni, Ghada, Arguello Casteleiro, Mercedes, Al Moubayed, Noura, Farrell, Sean O., Radford, Alan D., Noble, Peter-John M.
Publikováno v:
Frontiers in Veterinary Science; 2024, p1-7, 7p
Publikováno v:
JMIR Medical Informatics, Vol 3, Iss 1, p e4 (2015)
BackgroundPatients with multiple conditions have complex needs and are increasing in number as populations age. This multimorbidity is one of the greatest challenges facing health care. Having more than 1 condition generates (1) interactions between
Externí odkaz:
https://doaj.org/article/256e1ce5261e455d90decdb35594cdb7
Autor:
Arguello-Casteleiro, Mercedes, Stevens, Robert, Des-Diz, Julio, Wroe, Chris, Fernandez-Prieto, Maria, Maroto, Nava, Maseda-Fernandez, Diego, Demetriou, George, Peters, Simon, Peter-John Noble, Jones, Phil, Dukes-McEwan, Jo, Radford, Alan, Keane, John, Nenadic, Goran
Additional file 4. This file contains the SPARQL SELECT queries; their results appear in Tables 9 and 11.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc5c6bcc573e908aff50792f6da8a89a
Autor:
Arguello Casteleiro, Mercedes1, Klein, Julie2, Stevens, Robert1 Robert.Stevens@manchester.ac.uk
Publikováno v:
Journal of Biomedical Semantics. 6/4/2016, p1-7. 7p.
Akademický článek
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Autor:
ARGUELLO CASTELEIRO, Mercedes, MASEDA FERNANDEZ, Diego, DEMETRIOU, George, READ, Warren, FERNANDEZ PRIETO, Maria Jesus, DES DIZ, Julio, NENADIC, Goran, KEANE, John, STEVENS, Robert
Publikováno v:
Studies in Health Technology & Informatics; 2017, Vol. 235, p516-520, 5p, 1 Chart, 1 Graph
Autor:
Arguello Casteleiro, Mercedes1 m.arguello@manchester.ac.uk, Demetriou, George1 George.Demetriou@manchester.ac.uk, Read, Warren1 warren.read@manchester.ac.uk, Fernandez Prieto, Maria Jesus2 M.J.Fernandez@salford.ac.uk, Maroto, Nava3 mariadelanava.maroto@upm.es, Maseda Fernandez, Diego4 Diego.Maseda@mcht.nhs.uk, Nenadic, Goran1,5 g.nenadic@manchester.ac.uk, Klein, Julie6,7 julie.klein@inserm.fr, Keane, John1,5 john.keane@manchester.ac.uk, Stevens, Robert1 Robert.Stevens@manchester.ac.uk
Publikováno v:
Journal of Biomedical Semantics. 4/12/2018, Vol. 9 Issue 1, pN.PAG-N.PAG. 1p.
Autor:
Arguello Casteleiro, Mercedes, Maseda Fernandez, Diego, Demetriou, George, Read, Warren, Fernandez-Prieto, MJ, Des Diz, Julio, Nenadic, Goran, Keane, John, Stevens, Robert
We investigate the application of distributional semantics models for facilitating unsupervised extraction of biomedical terms from unannotated corpora.\ud Term extraction is used as the first step of an ontology learning process that aims to (semi-)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::0da450288dc058fd31599cf6516ecc30
Publikováno v:
Arguello Casteleiro, M, Klein, J & Stevens, R 2016, ' The Proteasix Ontology ', Journal of Biomedical Semantics, vol. 7, 33 . https://doi.org/10.1186/s13326-016-0078-9
Journal of Biomedical Semantics
Journal of Biomedical Semantics
Background The Proteasix Ontology (PxO) is an ontology that supports the Proteasix tool; an open-source peptide-centric tool that can be used to predict automatically and in a large-scale fashion in silico the proteases involved in the generation of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::b60b5ac39211374c97aa0cd5124ac992