Predicting disease severity in multiple sclerosis using multimodal data and machine learning.

Magi AndorraAna FreireIrati ZubizarretaNicole Kerlero de RosboSteffan D BosMelanie RinasEinar A HøgestølSigrid A de Rodez BenaventTone BergeSynne Brune-IngebretseFederico IvaldiMaria CellerinoMatteo PardiniGemma VilaIrene Pulido-ValdeolivasElena H Martinez-LapiscinaSara LlufriuAlbert SaizYolanda BlancoEloy Martinez-HerasElisabeth SolanaPriscilla Bäcker-KoduahJanina BehrensJoseph KuchlingSusanna AsseyerMichael ScheelClaudia ChienHanna ZimmermannSeyedamirhosein MotamediJosef Kauer-BoninAlex BrandtJulio Saez-RodriguezLeonidas G AlexopoulosFriedemann PaulHanne F HarboHengameh ShamsJorge OksenbergAntonio UccelliRicardo Baeza-YatesPablo Villoslada

Published in: Journal of neurology (2023)

Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of disability worsening.

Keyphrases

multiple sclerosis
machine learning
big data
electronic health record
artificial intelligence
high resolution
white matter
single cell
ms ms
chronic pain