ArticleFrontiers in neurology2020
Deep Learning-Based Method to Differentiate Neuromyelitis Optica Spectrum Disorder From Multiple Sclerosis.
Article in Frontiers in neurology, 2020. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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, 55 citations in OpenAlex.
- Artificial intelligence in central nervous system autoimmune diseases: from clinical decision support to mechanistic discovery and translation.EMBO molecular medicine · 2026Review
- Current Applications of Artificial Intelligence in Neuro-Ophthalmic Imaging: A Narrative Approach.Medical sciences (Basel, Switzerland) · 2026Review
- Multimodal MRI biomarkers and machine learning in neuromyelitis optica spectrum disorder: a review.Frontiers in neurology · 2026Review
- Predict disabling severe attacks in neuromyelitis optica spectrum disorders: warning symptoms and innovative machine learning models.Journal of translational medicine · 2025Article
- Comparing Lesion Volume Dynamics Between Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorder During Remission Using Machine-Learning Segmentation.Journal of clinical neurology (Seoul, Korea) · 2025Article
- The role of AI for MRI-analysis in multiple sclerosis-A brief overview.Frontiers in artificial intelligence · 2025Review
- Assessing the effectiveness of machine learning and deep learning in differentiating neuroimmunological diseases: a systematic review and meta-analysis.Frontiers in neurology · 2025Article
- Transforming Medical Imaging: The Role of Artificial Intelligence Integration in PACS for Enhanced Diagnostic Accuracy and Workflow EfficiencyCurrent medical imaging · 2025Review
- Enhancing classification of active and non-active lesions in multiple sclerosis: machine learning models and feature selection techniques.BMC medical imaging · 2024Article
- Current and future role of MRI in the diagnosis and prognosis of multiple sclerosis.The Lancet regional health. Europe · 2024Review
- Predicting disease-related MRI patterns of multiple sclerosis through GAN-based image editing.Zeitschrift fur medizinische Physik · 2024Article
- A joint model for lesion segmentation and classification of MS and NMOSD.Frontiers in neuroscience · 2024Article
- Predicting Antiseizure Medication Treatment in Children with Rare Tuberous Sclerosis Complex-Related Epilepsy Using Deep Learning.AJNR. American journal of neuroradiology · 2023Article
- Review
- Recognizing Pediatric Tuberous Sclerosis Complex Based on Multi-Contrast MRI and Deep Weighted Fusion Network.Bioengineering (Basel, Switzerland) · 2023Article
- Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorder using a deep learning model.Scientific reports · 2023Article
- An Atypical Presentation of Chronic Inflammatory Myelin Degeneration in Neuromyelitis Optica (NMO).Cureus · 2023Article
- Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective.Journal of neurology · 2023Review
- Combining Clinical and Genetic Data to Predict Response to Fingolimod Treatment in Relapsing Remitting Multiple Sclerosis Patients: A Precision Medicine Approach.Journal of personalized medicine · 2023Article
- Transformer-Based Deep-Learning Algorithm for Discriminating Demyelinating Diseases of the Central Nervous System With Neuroimaging.Frontiers in immunology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
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.