Longitudinal modeling of Post-COVID-19 condition over three years: A machine learning approach using clinical, neuropsychological, and fluid markers.
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| Title: | Longitudinal modeling of Post-COVID-19 condition over three years: A machine learning approach using clinical, neuropsychological, and fluid markers. |
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| Authors: | Walders J; Department of Neurology, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany., Wetz S; Department of Neurology, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany., Costa AS; Department of Neurology, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany.; JARA Brain Institute Molecular Neuroscience and Neuroimaging (INM-11), Research Centre Jülich and RWTH Aachen University, 52056, Aachen, Germany., Hofmann A; German Center for Neurodegenerative Diseases (DZNE), 72076, Tübingen, Germany.; Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University Hospital Tübingen, 72076, Tübingen, Germany., Schulz JB; Department of Neurology, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany.; JARA Brain Institute Molecular Neuroscience and Neuroimaging (INM-11), Research Centre Jülich and RWTH Aachen University, 52056, Aachen, Germany., Reetz K; Department of Neurology, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany. kreetz@ukaachen.de.; JARA Brain Institute Molecular Neuroscience and Neuroimaging (INM-11), Research Centre Jülich and RWTH Aachen University, 52056, Aachen, Germany. kreetz@ukaachen.de., Dadsena R; Department of Neurology, RWTH Aachen University, Pauwelsstraße 30, 52074, Aachen, Germany.; JARA Brain Institute Molecular Neuroscience and Neuroimaging (INM-11), Research Centre Jülich and RWTH Aachen University, 52056, Aachen, Germany. |
| Source: | Scientific reports [Sci Rep] 2026 Feb 14; Vol. 16 (1), pp. 6517. Date of Electronic Publication: 2026 Feb 14. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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