ReviewJournal of neurology2021
Artificial intelligence as an emerging technology in the current care of neurological disorders.
Review in Journal of neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06334796 (Phase 1 Trial of the Implementation of an Artificial Intelligence-powered Virtual Assistant for Emergency Triage in Neurology), which is not on this map. Cited by 74 papers, 4 of them syntheses that pooled it.
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.
Phase 1 Trial of the Implementation of an Artificial Intelligence-powered Virtual Assistant for Emergency Triage in Neurology
Who cites it
74 citing papers in PubMed, 4 syntheses or guidelines pooled it, 190 citations in OpenAlex.
- Artificial intelligence support for diagnosis of neurodevelopmental disorders during childhood: an umbrella review.Frontiers in psychiatry · 2026Pooled it
- A Systematic Review of Genetics- and Molecular-Pathway-Based Machine Learning Models for Neurological Disorder Diagnosis.International journal of molecular sciences · 2024Pooled it
- The Value of Applying Machine Learning in Predicting the Time of Symptom Onset in Stroke Patients: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2023Pooled it
- Machine learning prediction of motor function in chronic stroke patients: a systematic review and meta-analysis.Frontiers in neurology · 2023Pooled it
- Human-AI Interaction With AI-Assisted Tumor Overlays in Pediatric Whole-Body Magnetic Resonance Imaging: Exploratory Reader Study.JMIR human factors · 2026Article
- MINERVA: a public XAI-powered platform advancing multi-target discovery in Alzheimer's disease.Journal of cheminformatics · 2026Article
- A Neurosurgeon's Guide to Mobile Health Application Development With a Case Study for Cervical Myelopathy.Neurosurgery · 2026Article
- Review
- Neuroscientific therapies for subjective tinnitus.Journal of Zhejiang University. Science. B · 2026Review
- Identification of perception gaps between physicians and patients with neurological diseases and the prediction of these gaps using machine learning.Scientific reports · 2026Observational
- Brain-Computer Interfaces for Vision Recovery in Precortical Vision Loss.Eye and brain · 2026Review
- Review
- AI-powered neuroimaging markers: a new era in paediatric Leigh syndrome diagnosis.Annals of medicine and surgery (2012) · 2025Article
- Integrating artificial intelligence with nanodiagnostics for early detection and precision management of neurodegenerative diseases.Journal of nanobiotechnology · 2025Review
- Machine Learning in Myasthenia Gravis: A Systematic Review of Prognostic Models and AI-Assisted Clinical Assessments.Diagnostics (Basel, Switzerland) · 2025Review
- Progressive multiple sclerosis: Evaluating current therapies and exploring future treatment strategies.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025Review
- The Role of Neuroinflammation and Network Anomalies in Drug-Resistant Epilepsy.Neuroscience bulletin · 2025Review
- Traumatic Brain Injury and Artificial Intelligence: Shaping the Future of Neurorehabilitation-A Review.Life (Basel, Switzerland) · 2025Review
- AI and Neurology.Neurological research and practice · 2025Review
- Review
14 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) has influenced all aspects of human life and neurology is no exception to this growing trend. The aim of this paper is to guide medical practitioners on the relevant aspects of artificial intelligence, i.e., machine learning, and deep learning, to review the development of technological advancement equipped with AI, and to elucidate how machine learning can revolutionize the management of neurological diseases. This review focuses on unsupervised aspects of machine learning, and how these aspects could be applied to precision neurology to improve patient outcomes. We have mentioned various forms of available AI, prior research, outcomes, benefits and limitations of AI, effective accessibility and future of AI, keeping the current burden of neurological disorders in mind. DISCUSSION: The smart device system to monitor tremors and to recognize its phenotypes for better outcomes of deep brain stimulation, applications evaluating fine motor functions, AI integrated electroencephalogram learning to diagnose epilepsy and psychological non-epileptic seizure, predict outcome of seizure surgeries, recognize patterns of autonomic instability to prevent sudden unexpected death in epilepsy (SUDEP), identify the pattern of complex algorithm in neuroimaging classifying cognitive impairment, differentiating and classifying concussion phenotypes, smartwatches monitoring atrial fibrillation to prevent strokes, and prediction of prognosis in dementia are unique examples of experimental utilizations of AI in the field of neurology. Though there are obvious limitations of AI, the general consensus among several nationwide studies is that this new technology has the ability to improve the prognosis of neurological disorders and as a result should become a staple in the medical community.
conclusionAI not only helps to analyze medical data in disease prevention, diagnosis, patient monitoring, and development of new protocols, but can also assist clinicians in dealing with voluminous data in a more accurate and efficient manner.
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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.