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Big data and artificial intelligence applied to blood and CSF fluid biomarkers in multiple sclerosis

Authors: Comabella Lopez, Manuel; TUR, CARMEN; Arrambide, Georgina;

Big data and artificial intelligence applied to blood and CSF fluid biomarkers in multiple sclerosis

Abstract

Artificial intelligence (AI) has meant a turning point in data analysis, allowing predictions of unseen outcomes with precedented levels of accuracy. In multiple sclerosis (MS), a chronic inflammatory-demyelinating condition of the central nervous system with a complex pathogenesis and potentially devastating consequences, AI-based models have shown promising preliminary results, especially when using neuroimaging data as model input or predictor variables. The application of AI-based methodologies to serum/blood and CSF biomarkers has been less explored, according to the literature, despite its great potential. In this review, we aimed to investigate and summarise the recent advances in AI methods applied to body fluid biomarkers in MS, highlighting the key features of the most representative studies, while illustrating their limitations and future directions.

Country
Spain
Keywords

Big Data, Multiple Sclerosis, demyelinating, Demyelinating, Fluid biomarkers, Immunology, Sang, Esclerosi múltiple, FENÓMENOS Y PROCESOS::conceptos matemáticos::algoritmos::inteligencia artificial, DISEASES::Nervous System Diseases::Autoimmune Diseases of the Nervous System::Demyelinating Autoimmune Diseases, CNS::Multiple Sclerosis, ANATOMÍA::líquidos y secreciones::líquidos corporales::sangre, ANATOMÍA::líquidos y secreciones::líquidos corporales::líquido extracelular::líquido cefalorraquídeo, CHEMICALS AND DRUGS::Biological Factors::Biomarkers, Artificial Intelligence, Humans, COMPUESTOS QUÍMICOS Y DROGAS::factores biológicos::biomarcadores, multiple scleorsis (MS), INFORMATION SCIENCE::Information Science::Informatics::Medical Informatics::Medical Informatics Applications::Information Systems::Big Data, CIENCIA DE LA INFORMACIÓN::Ciencias de la información::informática::informática médica::aplicaciones de la informática médica::sistemas de información::macrodatos, fluid biomarkers, Intel·ligència artificial, deep learning, Dades massives, Deep learning, RC581-607, ENFERMEDADES::enfermedades del sistema nervioso::enfermedades autoinmunitarias del sistema nervioso::enfermedades autoinmunes desmielinizantes del SNC::esclerosis múltiple, ANATOMY::Fluids and Secretions::Body Fluids::Extracellular Fluid::Cerebrospinal Fluid, Marcadors bioquímics, PHENOMENA AND PROCESSES::Mathematical Concepts::Algorithms::Artificial Intelligence, machine learning and AI, Immunologic diseases. Allergy, Líquid cefaloraquidi, ANATOMY::Fluids and Secretions::Body Fluids::Blood, Biomarkers

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
Green
gold