AI and Neurological Rare & Neuroimmune Diseases ── 2026-11-03
New papers on neurological rare and neuroimmune diseases and AI, collected from journal feeds, PubMed (searched across all journals) and OpenAlex (a public index used instead of Google Scholar), judged by Jev (an AI that makes language judgements): original research, AI central, which of 9 disease groups, treatment or trials, and then ranked by importance up to a daily limit. Journals are not filtered by impact factor; each paper shows its journal's IF-equivalent (OpenAlex two-year mean citedness) and the date of that value. Each entry shows the full original abstract.
Read by disease: Basic research（0） · ALS（0） · Parkinson's（0） · Hereditary neurodegeneration（0） · Neuromuscular（0） · Multiple sclerosis（1） · NMOSD/MOGAD（0） · Myasthenia gravis（0） · Autoimmune encephalitis/CIDP/GBS（0）
Neurodegeneration and neuroimmunology research and AI
No new qualifying paper for this issue.
ALS: treatment, trials and AI
No new qualifying paper for this issue.
Parkinson's disease and parkinsonism: treatment, trials and AI
No new qualifying paper for this issue.
Hereditary neurodegenerative diseases: treatment, trials and AI
No new qualifying paper for this issue.
Neuromuscular diseases (muscular dystrophy, SMA): treatment, trials and AI
No new qualifying paper for this issue.
Multiple sclerosis: treatment, trials and AI
- Abstract
AIM: This study assessed to what extent ico brain ms , a commercially available artificial intelligence (AI)-assisted magnetic resonance imaging (MRI) volumetry software, detected disease activity in patients with clinically and radiologically stable relapsing multiple sclerosis (RMS), and estimated its impact on radiologists' assessments. PATIENTS AND METHODS: We retrospectively enrolled 111 RMS patients with two consecutive MRI scans at one year interval, without relapses, progression or radiological changes while remaining on stable therapy. MRI scans were analyzed by four radiologists acting independently, and by ico brain ms . The radiologists performed their assessments both without and with ico brain ms support and categorized patient status based on lesion and brain volume changes. RESULTS: Radiologists' detection of lesion activity non-significantly increased from 6.8% to 8.6% (McNemar p = 0.215; ordinal regression p = 0.06; sign-test p = 0.08) using ico brain ms . Detection of accelerated brain volume loss increased from 2.0% to 7.7% (all p p brain ms detected new or significantly enlarged lesions in 16.2% and accelerated brain volume loss in 6.3% of participants. CONCLUSION: AI-assisted MRI volumetry may support radiologists to detect subclinical disease activity in patients characterized as having stable disease. What is this study about? Multiple sclerosis, a heterogeneous disease affecting the brain and spinal cord, results in a wide range of visible and invisible symptoms. The disease course is largely unpredictable with potential development of progression over time. Careful monitoring is recommended, both clinically and radiologically. In the absence of clinical signs, subtle changes may be detected with regular imaging of the brain through magnetic resonance imaging (MRI) scans. In this study, we tested whether ico brain ms , an artificial intelligence (AI) tool, can help radiologists to assess scans and spot changes over time in the brain of patients who were clinically and radiologically stable. Four radiologists were asked to compare two MRI scans of 111 patients on 2 occasions, without and with additional information from the AI-tool. What were the results? The tool flagged new or growing lesions and accelerated brain volume loss in a number of patients. Based on information provided by the tool, radiologists slightly raised the identification of new or growing lesions, while significantly increasing the detection of accelerated brain volume loss. The tool also helped to achieve a higher level of agreement across the 4 participating radiologists. What do the results mean? The study shows that an AI-tool can support radiologists to detect changes in the brain of patients with multiple sclerosis, in the absence of clinical worsening. Nonetheless, the review by radiologists remains necessary and cannot be replaced by the AI tool on its own.
Journal IF-equivalent: 1.9 (OpenAlex 2-year mean citedness, value as of 2026-11-01, retrieved 2026-11-03; not the official Clarivate IF)Reference: D’hooghe MB, Fockaert N, Glibert N, Elands S, Elosegi JA, Etxeberria Izal A, et al. A Belgian study assessing relapsing multiple sclerosis activity through automated magnetic resonance imaging volumetry. Neurodegenerative Disease Management. 2026 Nov 1 [Epub ahead of print]. doi:10.1080/17582024.2026.2752856.Checked: Abstract only
See all 1 Multiple sclerosis papers →
NMOSD and MOGAD: treatment, trials and AI
No new qualifying paper for this issue.
Myasthenia gravis: treatment, trials and AI
No new qualifying paper for this issue.
Autoimmune encephalitis, CIDP and Guillain-Barre syndrome: treatment, trials and AI
No new qualifying paper for this issue.