Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/41629
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dc.contributor.authorSerrano, J Ignacio
dc.contributor.authorRomero, Juan P
dc.contributor.authorCastillo, Ma Dolores Del
dc.contributor.authorRocon, Eduardo
dc.contributor.authorLouis, Elan D
dc.contributor.authorBenito-León, Julián
dc.date.accessioned2019-08-02T09:53:41Z-
dc.date.available2019-08-02T09:53:41Z-
dc.date.issued2017
dc.identifier.citationSci Rep.2017 05;(7)1:2190
dc.identifier.urihttps://hdl.handle.net/20.500.12530/41629-
dc.description.abstractEssential tremor (ET) is one of the most prevalent movement disorders. Being that it is a common disorder, its diagnosis is considered routine. However, misdiagnoses may occur regularly. Over the past decade, several studies have identified brain morphometric changes in ET, but these changes remain poorly understood. Here, we tested the informativeness of measuring cortical thickness for the purposes of ET diagnosis, applying feature selection and machine learning methods to a study sample of 18 patients with ET and 18 age- and sex-matched healthy control subjects. We found that cortical thickness features alone distinguished the two, ET from controls, with 81% diagnostic accuracy. More specifically, roughness (i.e., the standard deviation of cortical thickness) of the right inferior parietal and right fusiform areas was shown to play a key role in ET characterization. Moreover, these features allowed us to identify subgroups of ET patients as well as healthy subjects at risk for ET. Since treatment of tremors is disease specific, accurate and early diagnosis plays an important role in tremor management. Supporting the clinical diagnosis with novel computer approaches based on the objective evaluation of neuroimage data, like the one presented here, may represent a significant step in this direction.
dc.language.isoeng
dc.rightsopenAccess-
dc.subject.meshAged
dc.subject.meshBrain Mapping
dc.subject.meshCase-Control Studies
dc.subject.meshCerebral Cortex
dc.subject.meshCognition
dc.subject.meshEssential Tremor
dc.subject.meshFemale
dc.subject.meshHumans
dc.subject.meshMagnetic Resonance Imaging
dc.subject.meshMale
dc.subject.meshMiddle Aged
dc.subject.meshNeuropsychological Tests
dc.subject.meshOrgan Size
dc.subject.meshData Mining
dc.titleA data mining approach using cortical thickness for diagnosis and characterization of essential tremor.
dc.typeArtículo
dc.identifier.pubmedID28526878
dc.format.volume7
dc.format.page2190
dc.identifier.e-issn2045-2322
dc.identifier.journalScientific reports
dc.identifier.doi10.1038/s41598-017-02122-3
dc.format.number1
dc.identifier.pmcPMC5438396
dc.pubmedtypeJournal Article
dc.pubmedtypeResearch Support, N.I.H., Extramural
dc.pubmedtypeResearch Support, Non-U.S. Gov't
Appears in Collections:Hospitales > H. U. 12 de Octubre > Artículos

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