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Longitudinal modeling of Post-COVID-19 condition over three years: A machine learning approach using clinical, neuropsychological, and fluid markers
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In
Scientific reports 16, Seiten/Artikel-Nr.:6517
2026
Online
DOI: 10.1038/s41598-026-37635-3
DOI: 10.18154/RWTH-2026-02568
URL: https://publications.rwth-aachen.de/record/1029763/files/1029763.pdf
Einrichtungen
- Klinik und Lehrstuhl für Neurologie (535000-2 ; 933810)
- JARA-Institut Molecular Neuroscience und Neuroimaging (080056)
Thematische Einordnung (Klassifikation)
DDC: 600
OpenAccess: 
PDF
Dokumenttyp
Journal Article
Format
online
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105030202478
WOS Core Collection: WOS:001693282000001
Interne Identnummern
RWTH-2026-02568
Datensatz-ID: 1029763
Beteiligte Länder
Germany
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; Article Processing Charges ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; Fees ; IF < 5 ; JCR ; PubMed Central ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection ; Zoological Record
| Typ | Amount | VAT | Currency | Share | Status | Cost centre |
| APC | 1929.91 | 135.09 | EUR | 95.69 % | (DEAL) | 021000-933810 |
| Other | 87.00 | 6.09 | EUR | 4.31 % | (DEAL) | 021000-933810 |
| Sum | 2016.91 | 141.18 | EUR | |||
| Total | 2158.09 |
Record created 2026-03-02, last modified 2026-06-12
OpenAccess:
PDF
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