ArticleFrontiers in neuroscience2017
Machine Learning Approach for Classifying Multiple Sclerosis Courses by Combining Clinical Data with Lesion Loads and Magnetic Resonance Metabolic Features.
Article in Frontiers in neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- SeruNet-MS: A Two-Stage Interpretable Framework for Multiple Sclerosis Risk Prediction with SHAP-Based Explainability.Neurology international · 2025Article
- A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.BMC medical imaging · 2025Article
- Noninvasive imaging biomarker reveals invisible microscopic variation in acute ischaemic stroke (≤ 24 h): a multicentre retrospective study.Scientific reports · 2025Article
- Machine learning for refining interpretation of magnetic resonance imaging scans in the management of multiple sclerosis: a narrative review.Royal Society open science · 2025Review
- Utilizing Aerobic Capacity Data for EDSS Score Estimation in Multiple Sclerosis: A Machine Learning Approach.Diagnostics (Basel, Switzerland) · 2024Article
- Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set.Human brain mapping · 2023Article
- MRI advances in the imaging diagnosis of tuberculous meningitis: opportunities and innovations.Frontiers in microbiology · 2023Review
- Accounting for uncertainty in training data to improve machine learning performance in predicting new disease activity in early multiple sclerosis.Frontiers in neurology · 2023Article
- Multiple sclerosis and computational biology (Review).Biomedical reports · 2022Review
- Multiple Sclerosis Diagnosis Using Machine Learning and Deep Learning: Challenges and Opportunities.Sensors (Basel, Switzerland) · 2022Review
- Developments in proton MR spectroscopic imaging of prostate cancer.Magma (New York, N.Y.) · 2022Review
- An Enhanced Multiple Sclerosis Disease Diagnosis via an Ensemble Approach.Diagnostics (Basel, Switzerland) · 2022Article
- Foundations of Lesion Detection Using Machine Learning in Clinical Neuroimaging.Acta neurochirurgica. Supplement · 2022Article
- Role of artificial intelligence in MS clinical practice.NeuroImage. Clinical · 2022Review
- A Novel Digital Care Management Platform to Monitor Clinical and Subclinical Disease Activity in Multiple Sclerosis.Brain sciences · 2021Article
- Machine Learning Approaches in Study of Multiple Sclerosis Disease Through Magnetic Resonance Images.Frontiers in immunology · 2021Review
- Dynamic Functional Connectivity Better Predicts Disability Than Structural and Static Functional Connectivity in People With Multiple Sclerosis.Frontiers in neuroscience · 2021Article
- Model-Driven Decision Making in Multiple Sclerosis Research: Existing Works and Latest Trends.Patterns (New York, N.Y.) · 2020Review
- Artificial Intelligence in Neuroradiology: Current Status and Future Directions.AJNR. American journal of neuroradiology · 2020Article
- Inferring Multiple Sclerosis Stages from the Blood Transcriptome via Machine Learning.Cell reports. Medicine · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.