Integrated Biomarker–Volumetric Profiling Defines Neurodegenerative Subtypes and Predicts Neuroaxonal Injury in Multiple Sclerosis Based on Bayesian and Machine Learning Analyses

<b>Background</b>: The clinical–radiological paradox in multiple sclerosis (MS) underscores the need for biomarkers that better reflect neurodegenerative pathology. Serum neurofilament light chain (sNfL) is a dynamic marker of neuroaxonal injury, while brain volumetry provides structural assessment...

Full beskrivning

Bibliografiska uppgifter

Huvudupphov:	Alin Ciubotaru, Roxana Covali, Cristina Grosu, Daniel Alexa, Laura Riscanu, Bîlcu Robert-Valentin, Radu Popa, Gabriela Dumachita Sargu, Cristina Popa, Cristiana Filip, Laura-Elena Cucu, Albert Vamanu, Victor Constantinescu, Emilian Bogdan Ignat
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2025-12-01
Serie:	Biomedicines
Ämnen:	multiple sclerosis serum neurofilament light chain brain volumetry Bayesian analysis machine learning endophenotypes
Länkar:	https://www.mdpi.com/2227-9059/14/1/42
Taggar:	Lägg till en tagg Inga taggar, Lägg till första taggen!