Machine learning-driven diagnosis of multiple sclerosis from whole blood transcriptomics-Reference-Cited by-同舟云学术

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Machine learning-driven diagnosis of multiple sclerosis from whole blood transcriptomics

Published:2024-10 Issue: Volume:121 Page:269-277
ISSN:0889-1591
Container-title:Brain, Behavior, and Immunity
language:en
Short-container-title:Brain, Behavior, and Immunity

Author:

Omrani Maryam,Chiarelli Rosaria Rita,Acquaviva Massimo,Bassani Claudia,Dalla Costa Gloria,Montini Federico,Preziosa Paolo,Pagani Lucia,Grassivaro Francesca,Guerrieri Simone,Romeo Marzia,Sangalli Francesca,Colombo Bruno,Moiola Lucia,Zaffaroni Mauro,Pietroboni Anna,Protti Alessandra,Puthenparampil Marco,Bergamaschi Roberto,Comi Giancarlo,Rocca Maria A.,Martinelli Vittorio,Filippi Massimo,Farina Cinthia

Funder

Ministero della Salute

Publisher

Elsevier BV

Reference46 articles.

1. Inferring Multiple Sclerosis Stages from the Blood Transcriptome via Machine Learning;Acquaviva;Cell Reports Medicine,2020

2. Molecular-based diagnosis of multiple sclerosis and its progressive stage;Barbour;Ann. Neurol.,2017

3. The Economic Burden of Multiple Sclerosis in the United States;Bebo;Neurology,2022

4. MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry;Bendfeldt;Brain Imaging Behav.,2019

5. Role of artificial intelligence in MS clinical practice;Bonacchi;NeuroImage: Clinical,2022

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