{"?xml":{"@version":"1.0"},"edm:RDF":{"@xmlns:dc":"http://purl.org/dc/elements/1.1/","@xmlns:edm":"http://www.europeana.eu/schemas/edm/","@xmlns:wgs84_pos":"http://www.w3.org/2003/01/geo/wgs84_pos","@xmlns:foaf":"http://xmlns.com/foaf/0.1/","@xmlns:rdaGr2":"http://rdvocab.info/ElementsGr2","@xmlns:oai":"http://www.openarchives.org/OAI/2.0/","@xmlns:owl":"http://www.w3.org/2002/07/owl#","@xmlns:rdf":"http://www.w3.org/1999/02/22-rdf-syntax-ns#","@xmlns:ore":"http://www.openarchives.org/ore/terms/","@xmlns:skos":"http://www.w3.org/2004/02/skos/core#","@xmlns:dcterms":"http://purl.org/dc/terms/","edm:WebResource":[{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:DOC-EV512K41/64a17841-4b08-4e26-8313-c4ad203b6c32/PDF","dcterms:extent":"149 KB"},{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:DOC-EV512K41/ef588c90-1b02-43fd-9838-86c1d30b294a/TEXT","dcterms:extent":"19 KB"}],"edm:ProvidedCHO":{"@rdf:about":"URN:NBN:SI:DOC-EV512K41","dcterms:issued":"2023","dc:creator":["Brecl Jakob, Gregor","Dular, Lara","Magdič, Jožef","Rojc, Bojan","Savšek, Lina","Špiclin, Žiga"],"dc:format":{"@xml:lang":"sl","#text":"Str. 51-57"},"dc:identifier":["ISSN:0353-3484","COBISSID_HOST:149964803","URN:URN:NBN:SI:doc-EV512K41"],"dc:language":"sl","dc:publisher":{"@xml:lang":"sl","#text":"Medicinski razgledi"},"dc:source":{"@xml:lang":"sl","#text":"Medicinski razgledi (Supplement)"},"dc:subject":[{"@xml:lang":"sl","#text":"analiza MR-slik"},{"@xml:lang":"en","#text":"machine learning of prognostic models"},{"@xml:lang":"en","#text":"MR image analysis"},{"@xml:lang":"sl","#text":"napovedovanje poteka multiple skleroze"},{"@xml:lang":"en","#text":"prognosis of multiple sclerosis disease course"},{"@xml:lang":"sl","#text":"strojno učenje napovednih modelov"}],"dc:title":{"@xml:lang":"sl","#text":"Napovedovanje kliničnega poteka multiple skleroze iz magnetnoresonančnih slik| predhodni rezultati raziskave| preliminary study results| The prediction of multiple sclerosis disease course from magnetic resonance images|"},"dc:description":{"@xml:lang":"sl","#text":"Backgrounds. Early identification of multiple sclerosis patients at risk of disease progression and/or progression to secondary progressive multiple sclerosis is an important unmet clinical need. This research aimed to train and evaluate predictive models of disability progression in patients with multiple sclerosis from MR images. Methods. The volumes of 268 brain structures and the volume and number of white matter lesions were determined from T1-enhanced and water-attenuated MR images through the automatic analysis of these images. We used these measurements to train three established classifier models, while the fourth model was based on a convolutional neural network and was trained directly on the gray values of MR images. Results. The fourth model achieved the best area under the receiver operating characteristic curve value of 74%, the accuracy of 76% and sensitivity of 51%, and the random forest classifier-based model achieved the highest sensitivity of 54%. The stated results are consistent with the results of previous research. Discussion. The ability to identify increased risk of disability progression from MR images is a promising research direction. Further improvements in predictive models would enable early intervention to prevent or delay the progression of disability and/or the transition to secondary progressive multiple sclerosis"},"edm:type":"TEXT","dc:type":[{"@xml:lang":"sl","#text":"znanstveno časopisje"},{"@xml:lang":"en","#text":"journals"},{"@rdf:resource":"http://www.wikidata.org/entity/Q361785"}]},"ore:Aggregation":{"@rdf:about":"http://www.dlib.si/?URN=URN:NBN:SI:DOC-EV512K41","edm:aggregatedCHO":{"@rdf:resource":"URN:NBN:SI:DOC-EV512K41"},"edm:isShownBy":{"@rdf:resource":"http://www.dlib.si/stream/URN:NBN:SI:DOC-EV512K41/64a17841-4b08-4e26-8313-c4ad203b6c32/PDF"},"edm:rights":{"@rdf:resource":"http://rightsstatements.org/vocab/InC/1.0/"},"edm:provider":"Slovenian National E-content Aggregator","edm:intermediateProvider":{"@xml:lang":"en","#text":"National and University Library of Slovenia"},"edm:dataProvider":{"@xml:lang":"sl","#text":"Društvo Medicinski razgledi"},"edm:object":{"@rdf:resource":"http://www.dlib.si/streamdb/URN:NBN:SI:DOC-EV512K41/maxi/edm"},"edm:isShownAt":{"@rdf:resource":"http://www.dlib.si/details/URN:NBN:SI:DOC-EV512K41"}}}}