Random forest analysis of midbrain hypometabolism using [18F]-FDG PET identifies Parkinson’s disease at the subject-level

Random forest analysis of midbrain hypometabolism using [18F]-FDG PET identifies Parkinson’s disease at the subject-level

Parkinson’s disease (PD) is currently diagnosed largely on the basis of expert judgement with neuroimaging serving only as a supportive tool. In a recent study, we identified a hypometabolic midbrain cluster, which includes parts of the substantia nigra, as the best differentiating metabolic feat...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Päätekijät: Ruppert-Junck, Marina Christine, Kräling, Gunter, Greuel, Andrea, Tittgemeyer, Marc, Timmermann, Lars, Drzezga, Alexander, Eggers, Carsten, Pedrosa, David
Aineistotyyppi: Artikkeli
Kieli:englanti
Julkaistu: Philipps-Universität Marburg 2024
Aiheet:
Parkinson’s disease
random forest
metabolic imaging
imaging biomarker
machine learning
Medizin
Medical sciences Medicine
Linkit:PDF-kokoteksti
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Internet

PDF-kokoteksti

Saatavuus:
Hyllypaikka: urn:nbn:de:hebis:04-es2024-08659
Julkaisupäivä: 2024-04-18
Lähde: Erstveröffentlichung: Ruppert-Junck MC, Kräling G, Greuel A, Tittgemeyer M, Timmermann L, Drzezga A, Eggers C and Pedrosa D (2024
Downloads: 6 (2024)
Lizenz: https://creativecommons.org/licenses/by/4.0
Linkki aineistoon: https://archiv.ub.uni-marburg.de/es/2024/0865
https://doi.org/10.3389/fncom.2024.1328699

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