Role of artificial intelligence in MS clinical practice-Reference-Cited by-同舟云学术

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Role of artificial intelligence in MS clinical practice

Published:2022 Issue: Volume:35 Page:103065
ISSN:2213-1582
Container-title:NeuroImage: Clinical
language:en
Short-container-title:NeuroImage: Clinical

Author:

Bonacchi Raffaello,Filippi Massimo,Rocca Maria A.

Funder

Bristol-Myers Squibb Canada

Bayer

Biogen

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology (clinical),Neurology,Radiology, Nuclear Medicine and imaging

Reference137 articles.

1. Inferring multiple sclerosis stages from the blood transcriptome via machine learning;Acquaviva;Cell Rep. Med.,2020

2. The emerging role of artificial intelligence in multiple sclerosis imaging;Afzal;Mult. Scler.,2020

3. Deep learning for brain MRI segmentation: state of the art and future directions;Akkus;J. Digit. Imaging,2017

4. Metabolome-based signature of disease pathology in MS;Andersen;Mult. Scler. Relat. Disord.,2019

5. Multi-branch convolutional neural network for multiple sclerosis lesion segmentation;Aslani;Neuroimage,2019

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1. Machine learning-driven diagnosis of multiple sclerosis from whole blood transcriptomics;Brain, Behavior, and Immunity;2024-10

2. Consensus of algorithms for lesion segmentation in brain MRI studies of multiple sclerosis;Scientific Reports;2024-09-12

3. Mass Spectrometry Advancements and Applications for Biomarker Discovery, Diagnostic Innovations, and Personalized Medicine;International Journal of Molecular Sciences;2024-09-12

4. AI supported detection of cerebral multiple sclerosis lesions decreases radiologic reporting times;European Journal of Radiology;2024-09

5. Deep Learning-based Methods for MS Lesion Segmentation: A Review;2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP);2024-07-11

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